Ant diversity partitioning across spatial scales: Ecological processes and implications for conserving Tropical Dry Forests

Ant diversity partitioning across spatial scales:Ecological processes and implications for conservingTropical Dry Forests

TATIANNE MARQUES1* AND JOSÉ H. SCHOEREDER2

1Programa de Pós-Graduação em Entomologia, Departamento de Entomologia, Universidade Federal deViçosa, Viçosa, MG, 36570-000, Brazil (Email: [email protected]), and 2Departamento de BiologiaGeral, Universidade Federal deViçosa, Viçosa, Minas Gerais, Brazil

Abstract Several ecological and evolutionary processes can drive changes in diversity at different spatial scales.To determine the scale at which these processes are most influential, we hypothesized that (i) broad-scaledifferences between ecoregions had greater influence on ant species richness and species turnover than localdifferences among fragments within ecoregions; and (ii) the degree of dissimilarity in ant species composition islarger between Tropical Dry Forest fragments and the surrounding vegetations than among Tropical Dry Forestslocated in different ecoregions, indicating that extant Tropical Dry Forests are relicts of a broader distributionof this vegetation. To examine ant diversity patterns, we built a nested hierarchical design on three spatialscales, ranging from fragments (local scale), Tropical Dry Forest + surroundings vegetation (landscape scale) andBrazilian ecoregions (regional scale). We used 450 sampling units (45 sampling units ¥ two fragments ¥ fiveecoregions = 450). A null model based on the sample was used to identify variations in the random distributionacross spatial scales. Spatial partitioning of ant diversity showed that observed b1 diversity (between fragments) andb2 diversity (among ecoregions) were higher than expected by chance. When the partitioning was analysedseparately for each region, the observed b1 diversity (Tropical Dry Forest and surrounding vegetation) was higherthan expected by the null hypothesis in all ecoregions of Brazil. Based on species composition and diversitypatterns, we stress the importance of creating more protected areas throughout the coverage area of Tropical DryForests, favouring a more efficient conservation process.

Key words: diversity partitioning, Formicidae, local–regional richness, species composition, Tropical Dry Forest.

INTRODUCTION

Biodiversity is typically distributed in a heterogene-ous fashion among habitats, landscapes and regions.Understanding how and why the spatial distribution ofspecies diversity changes between spatial scales areamong the main interests of ecological theory (Ricklefs2004). The pervasiveness of scale dependency (Wiens1989) is a key factor limiting the generality of ecologi-cal patterns and processes (Lawton 1999). Choosinga single spatial scale as the main focus of study canlead to conclusions with limited explanatory power,as distinct patterns may result from studies on otherscales (Summerville et al. 2003). To determine therelative importance of different processes drivingspecies diversity, it is important to collect standardizeddata at comparable spatial scales, repeating thisprocess across different scales (Whittaker et al. 2001).

Several researchers have noted the importanceof spatial scales to ant communities (Lawton 1999;

Gotelli & Ellison 2002; Parr et al. 2005; Spiesman &Cumming 2008), but there have been few studiesdesigned to test this importance (Kaspari et al. 2003;Campos et al. 2011; Pacheco & Vasconcelos 2012).Leal et al. (2012) found that factors acting on the localscale, such as vegetation structure, are more importantto the ant regional pool of species in the AtlanticForest, while landscapes contributed less than 5% togamma diversity.

In their attempts to understand how ant diversity isinfluenced by spatial variation, previous researcherssuggested several hypotheses to explain the influenceof spatial scales on ant diversity and communitycomposition. At the local scale (i.e. within-forest frag-ments), tree density and species richness determinethe arboreal ant species richness (Ribas et al. 2003). Incontrast, processes at intermediate scales (among frag-ments, within a region), the structural heterogeneityof the vegetation and geographic separation of forestfragments become more important to species diversityand composition (Campos et al. 2011; Pacheco &Vasconcelos 2012). At the broader spatial scale (ecore-gions or continents), biogeographic and evolutionary

*Corresponding author.Accepted for publication March 2013.

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© 2013 The Authors doi:10.1111/aec.12046Austral Ecology © 2013 Ecological Society of Australia

history may be important in determining ant speciesrichness (Ribas et al. 2003; Campos et al. 2011).Theseobservations suggest that species aggregations withinhabitats, landscapes, and regions are important instructuring ant communities, but species aggregationpatterns may differ across scales. In theory, local antspecies richness may result from the transition ofspecies through a series of filters, which represent eco-logical processes regulating diversity at different scales(Hillebrand & Blenckner 2002; Fig. 1).

Since the seminal paper by Lande (1996), researchworks have provided an excellent and updated over-view of approaches to decomposing diversity (Wagneret al. 2000; Veech et al. 2002; Crist et al. 2003; Geringet al. 2003; Forum in Ecology (Ellison 2010 and papersfollowing it); Chao et al. 2012). Many authors agreethat additive partitioning of diversity is a promisingmethodological approach to better understandingdiversity patterns at multiple spatial scales, whichallows the researcher to identify the scale that mostcontributes to the regional pool of species. We agreethat additive partitioning gives more friendly unitsthan the more classic multiplicative partitioning,because all diversity estimates are represented inthe same unit (species number), facilitating datainterpretation.

Processes at some spatial scales might have largerrelative effects on community structure than others(Wagner et al. 2000; Summerville et al. 2003; Camposet al. 2011). Identifying critical scales is of greatimportance for successfully conserving forest biodiver-sity (Ehrlich 1996). For example, if local processessuch as tree species richness effects are the most

important factors determining ant diversity, thenconservation initiatives should be directed towardmaintaining floristic heterogeneity within fragments.In contrast, if broad-scale ecoregional effects predomi-nate, then successful biodiversity conservation willultimately depend on creating a regionally stratified setof natural areas, with preservation efforts spread acrossas many ecoregions as possible (Summerville et al.2003).

In areas with a high degree of human disturbance,such as Tropical Dry Forests (TDFs) (Miles et al.2006; Portillo-Quintero & Sanchez-Azofeifa 2010),conservation strategies should be directed towardprotecting the remaining habitats, considering theregional species distribution patterns across differentspatial scales (Brown & Freitas 2000; Fahrig 2003).TDFs occur in discontinuous patches scatteredthroughout Brazil (see Appendix S1) and are foundwithin various vegetation types depending on localclimate, soil, and topographic conditions (Penningtonet al. 2009). These attributes characterize the regionswhere TDF fragments are located as heterogeneouslandscapes that should support more species diversitythan those consisting of a single homogenous habitat.

The aim of this paper is to identify the spatial scalethat contributes most to the regional pool of antspecies. The hypotheses tested were: (i) broad-scaledifferences among ecoregions are more important ininfluencing ant species richness and species turnoverthan are local differences among fragments withinecoregions; and (ii) the degree of dissimilarity in antspecies composition is larger between TDF fragmentsand surrounding vegetation than among TDFs in

Fig. 1. Schematic model of the passage of species through selective ‘filters’, spatial scale dependent. Each filter represents theaction of ecological processes in determining the biological diversity of a community (adapted from Hillebrand & Blenckner2002).

2 T. MARQUES AND J. H. SCHOEREDER

© 2013 The Authorsdoi:10.1111/aec.12046Austral Ecology © 2013 Ecological Society of Australia

different ecoregions, indicating that extant TDFs arerelicts of a broader distribution of this vegetation.

MATERIALS AND METHODS

Differentiating TDFs fromsurrounding vegetation

Brazil is a mega-diverse country (Lewinsohn & Prado 2005)covered by various biomes: tropical rain forests (mostly inthe Amazon and Atlantic regions), savannas (Cerrado veg-etation), wetlands (Pantanal), grasslands (Pampas), aridand semi-arid lowlands (Caatinga vegetation and TDF)(Pennington et al. 2000). TDFs are in contact with all Bra-zilian biomes (Appendix S1) and one fragment of eachbiome represents the surrounding vegetation sampled in thisstudy. Collectively, TDF, Caatinga, Cerrado, Pantanal, andPampas represent a wide range of seasonal ecosystems (fromSeasonally Dry Tropical Forest to grasslands), which covernearly 50% of Brazilian territory (Santos et al. 2011). Humidor less seasonal ecosystems are represented by two immenseblocks of tropical forest (Amazonia and Atlantic Forest),which cover the other half of the Brazilian territory (Santoset al. 2011).

Among the biomes that have marked seasonality are TDF,Caatinga and Cerrado, each of which is distinguished byspecific characteristics. TDFs are broadly defined as forestsoccurring in tropical regions marked by prominent seasonalrainfall, with several months of severe drought (Mooney et al.1995). Decisive biophysical and climatic factors include soilswith high nutrient content and moderate to high pH. Theseoccur in frost-free regions with seasonal rainfall of less than1600 mm year-1, with at least 5–6 months receiving less than100 mm (Murphy & Lugo 1986; Pennington et al. 2006).The average annual temperature of these forests is greaterthan 25°C (Sanchez-Azofeifa et al. 2005).TDFs have a lowercanopy and basal area than tropical rain forests (Murphy &Lugo 1986) and present heterogeneous vegetation rangingfrom tall forests to cactus scrub, but are mostly tree-dominated and semi-deciduous to deciduous during the dryseason (Murphy & Lugo 1986; Pennington et al. 2006).

The Caatinga covers most of the ‘Depressão Sertaneja’, agreat extent of semi-arid lowlands (<400 m.a.s.l) with emerg-ing tablelands, highland ridges and sandy deposits, with con-trasting climates and vegetation types, including Cerrado(savanna woodlands), Campos Rupestres (rocky grass andscrublands), and TDFs (Santos et al. 2011, 2012). It is com-posed mostly of succulent (e.g. cacti) and non-succulentshrubs and trees, most of which are armed with either thornsor prickles and bear microphyllous foliages, though they areleafless during the long drought periods. The ground layeris rich in bromeliads, annual herbs, and geophytes (Santoset al. 2011).

The Cerrado is a savanna woodland physiognomy, whichoccupies most of central Brazil (Pennington et al. 2009).Savannas are found under similar or slightly wetter climatesthan TDFs, and these two biomes can coexist in closeproximity. Savanna trees frequently have sclerophyllous,leaves that remain evergreen because of the nutrient-limitedsoils (Ratter et al. 1997). Succulent species are almost

entirely absent from savannas, probably because they are notadapted to fire, which is a frequent and natural disturbancein this biome.

Sampling design

We used a hierarchical nested design to sample ants acrossdifferent spatial scales. We followed the spatial scale defini-tions of Santos et al. (2008) for ant assemblages, which con-sidered a local scale as an area large enough for ant species toestablish their nests, forage and interact with neighbouringorganisms and the abiotic surroundings.The landscape scaleis larger than local and on this scale, dispersal and migrationprocesses may occur over ecological time.The regional scaleis larger than the previous two and on this scale extinctionand colonization processes are more important to the struc-ture of ant communities.

All three hierarchical levels were represented in thisdesign. The regional scale was represented by the fivesampled Brazilian ecoregions, landscape by each ecoregionstudied (TDF + surrounding vegetation), and local by frag-ments (Table 1).

At the regional scale we selected five Brazilian ecoregionsin different biomes in which TDFs fragments are located(Table 1): (1) Atlantic Forest in Bahia State (BA), (2) Caat-inga in Minas Gerais State (MG), (3) Cerrado in Goiás State(GO), (4) Pantanal in Mato Grosso do Sul State (MS) and(5) Southern Plains, the Pampas, located in Rio Grande doSul State (RS). We followed the assessment by Olson et al.(2001) and Instituto Brasileiro do Meio Ambiente e dosRecursos Naturais Renováveis (IBAMA, http://www.ibama.gov.br/ecossistemas/ecoregioes.htm) for the delineation ofecoregions.

At the landscape scale we selected a TDF fragment and afragment consisting of the surrounding vegetation in eachecoregion, totalling 10 patches.The landscapes are located in(Table 1): (1) Independence Farm, Itambé, Bahia – BA; (2)Parque Estadual Mata Seca – PEMS, Manga, Minas Gerais– MG; (3) Sabonete Farm, Posse, Goiás – GO; (4) ParqueNacional da Serra Bodoquena, Bodoquena, Mato Grossodo Sul – MS; (5) Parque Estadual do Turvo, Derrubadas,Rio Grande do Sul – RS.

In each fragment we distributed 15 sampling points.In each sampling point, we installed pitfall traps to collectthe ants, each one at arboreal, epigaeic (ground level) andhypogaeic (underground) microhabitats, totalling 45 sam-pling units per fragment. Thus, the local scale was repre-sented by cumulative species richness in the 45 samplingunits of each fragment. In this study we obtained a total of450 sampling units (45 sampling units ¥ two fragments ¥five ecoregions = 450).

Ant sampling

Ant sampling was carried out once in each fragment,between the months of January and May in 2008 and 2009,always near the rainy season in each region.We distributed 15sampling points in each fragment, 15 m apart from eachother. At each sampling point, in the hypogaeic, epigaeic and

ANT DIVERSITY PAR TITIONING 3


arboreal microhabitats, we installed pitfall traps baited withsardines and honey. Sampling ants in different strata of theforest results in a better estimative of the total diversity of antcommunities of the fragments studied. For testing the com-pleteness of the sampling, we calculated the adequacy of thesampling effort with a species accumulation curve.The arbo-real pitfall traps follow the description by Ribas et al. (2003),with the epigaeic trap similar to the arboreal but buried withthe opening of the container at the ground level, and thehypogaeic trap was as described by Schmidt and Solar(2010).

Pitfall traps have been shown to collect a representativesample of ants in tropical forests (Barrow & Parr 2008;Andersen et al. 2010; Frizzo et al. 2012; Ribas et al. 2012;Schmidt et al. 2013).With small adjustments in conventionalpitfall traps (i.e. pitfall traps placed on the soil surface),this is an effective and unbiased method to collect arborealants (Neves et al. 2010; Cerdá et al. 2012), epigaeic ants(Andersen 1991; Chen et al. 2011) and hypogaeic ants(Schmidt & Solar 2010) in this forests.

The traps remained in the field for 48 h and were subse-quently removed and taken to the laboratory for sorting,mounting and ant identification. Ants were sorted to genus,then to species or morphospecies. Ant nomenclature followsBolton et al. (2007). Voucher specimens were deposited atthe reference collection at the Laboratory of CommunityEcology at the Universidade Federal de Viçosa (UFV), inViçosa, Brazil.

Data analyses

We constructed the species accumulation curves using thenumbers of species and the number of pitfall traps sampled,performing 10 000 randomizations with replacement togenerate confidence intervals using the vegan package in R2.11.1 software (R Development Core Team 2010).

Using permutational multivariate analysis of variance(PERMANOVA, Anderson 2001) we tested the influence ofecoregions, fragments (TDFs and their surroundings) and

their interaction on ant community composition, using theJaccard dissimilarity measure and 999 permutations. PER-MANOVA is a permutational anova, which was developed totest the simultaneous response of one or more variables toone or more factors in analyses of variance (anova). A per-mutational multivariate analysis of dispersion (PERMDISP)was then run on this Jaccard dissimilarity matrix to test thedifferences in the homogeneity of ant assemblages acrossecoregions and fragments (Anderson 2001, 2006). PERM-DISP compares the distances from observations to theirgroup centroid (analogous to a measure of variance) and thusallowed us to compare the heterogeneity of ant communitybetween ecoregions and fragments. The PERMANOVAused the ‘adonis’ procedure and the PERMDISP used the‘betadisper’ procedure in the vegan package in R. Ordina-tions were plotted with non-metric multidimensional scaling(NMDS) using the vegan’s ‘metaMDS’ procedure in R.

We used additive partitioning as a tool to partition totalant diversity (gamma) into its alpha and beta components.The diversity is aggregated into hierarchical levels that have450 (sampling points), 10 (fragments) and five (ecoregions ofBrazil) units.The total species richness (g) found in a collec-tion of samples of any spatial scale can be partitioned intothe average number of species occurring within a sample (a)and the average number of species absent from a sample,but present in another sample (b; Veech et al. 2002). Then,g = a + b, and beta diversity can be estimated by b = g - a(Wagner et al. 2000). The diversity components are calcu-lated as bm = g - am for the largest spatial scale studied andbi = ai + 1 - ai for each inferior spatial scale, considering ahierarchical design with i = 1, 2, 3, . . . m sampling levels.

In this hierarchical study, total observed diversity gobs canbe partitioned as:

γ α β βobs F E= + +

Where a is the mean a-diversity per fragment, bF is thebetween-fragments b-diversity and bE the mean between-ecoregion b-diversity. In additive partitioning, alpha, betaand gamma components have the same unit: number ofspecies.

Table 1. Descriptions of the five ecoregions located in different biomes, habitats (Tropical Dry Forest –TDF and surroundingvegetation), area, elevation, mean monthly temperature and precipitation, and geographic coordinates

Site Biomes Ecoregion Habitat Area (ha)Elevation(m a.s.l)

Meanprecipitacion

(mm)

Meantemperature

(Co) Coordinates

1 AtlanticForest

BA TDF 100 245 83 24 15°42′39″S, 39°34′08″WAtlantic Forest

2 Caatinga MG TDF 15 466.44 493 90.5 25.1 14°97′02″S, 43°97′02″WArboreal Caatinga

3 Cerrado GO TDF 100 677 140 23 14°03′53″S, 46°29′15″WGrasslands

4 Pantanal MS TDF 77 232 413 142.8 27.3 20°46′56″S, 56°44′31″WRiparian Forest

5 Pampas RS TDF 17 491.40 200 150.6 21.4 27°14′06″S, 53°58′36″WSemideciduousSeasonal Forest

The climate data were obtained from WorldClim 1.4 database.



To compare the relative importance of each value of betadiversity we used a null model. Crist et al. (2003) describedtwo types of null models for additive partitioning of diver-sity. Model I (‘individual-based randomization’) randomizesindividuals among samples from all hierarchical levels ofstudy. Model II (‘sample-based randomization’) randomizesL-1 level samples into the L level, maintaining the numberof individuals and species present in each sampling unit.This form of data randomization preserves the pattern ofintraspecific aggregation at each scale, unlike model I. Inmodel II, the statistical significance of each component ofdiversity is tested using a separate set of randomizations foreach level L of the study. This procedure is performedbecause each hierarchical level presents a different numberof samples. As a result of this form of data randomization,the expected values of a1 and bi are not additive to totaldiversity (Crist et al. 2003). We decided to use model II,because part of beta diversity may result from samplingvariation, that is, the partition observed may be the result ofthe hierarchical sampling design (Crist et al. 2003). Datawere randomized 1000 times to generate the expected dis-tribution of the components of diversity under the nullmodel.

The differentiation of diversity components estimatedfrom observed values indicates that the spatial distribution ofspecies diversity is heterogeneous. If the mean observeddiversity is greater than expected among the study sites, thismay be the result of a strong variation within some of thesites, while other sites may show a pattern of diversity similarto the null model. Alternatively, if the mean observed diver-sity is equal to that expected by the null model, this resultmay be because of considerable negative deviations at somesites, which are counterbalanced by high and positive devia-tions from other sites. Therefore, besides carrying out thepartition of the whole ant community, we also calculated thecomponents of diversity at each hierarchical level of eachseparate ecoregion of Brazil. In these five independent analy-ses, gamma diversity was defined as the total number ofspecies sampled in each ecoregion. All tests were performedusing R with the package boot 1.2–42 (Canty & Ripley 2006).The routines for data analysis were developed by Ribeiroet al. (2008).

RESULTS

Ant fauna

We collected 163 ant species from 44 genera. Thesubfamily with the highest diversity was Myrmicinae(76 species), followed by Formicinae (40 species),Ponerinae (15 species), Dolichoderinae (12 species),Pseudomyrmecinae (nine species), Ectatomminae(five species), Ecitoninae (four species) and Cera-pachyinae with two ant species (see Appendix S2).Regarding the diversity of ants in different ecoregionsof Brazil, we collected 49 species of ants in MG (11species found in both forest fragments), 84 species inMS (20 in both fragments), 43 species in GO (10 inboth fragments), 46 species in RS (13 in both frag-ments) and 56 ant species in Bahia (14 in bothfragments). We collected 48 ant species unique to theTDFs and 29 species exclusive to the surroundingenvironments.

In the species accumulation curve we observed atendency to an asymptote, indicating that the samplingeffort was sufficient (Fig. 2). These data suggest thatthe number of ant species sampled is close to the totalnumber of species in each ecoregion.

Changes in ant community

The ant community composition changes betweenfragments (Permanova, P < 0.001, Table 2) andecoregions of Brazil (Permanova, P < 0.001, Table 2),that is, the position of centroids differed. Moreover,there was significant Fragments*Ecoregion interaction(Permanova, P < 0.001, Table 2). When we consideronly TDF fragments, ant composition differed signi-ficantly between ecoregions (Permanova, P < 0.001,Table 2, Fig. 3). Permdisp revealed significantly

0 20 40 60 80

020

4060

80

Number of pitfalls sampled

Spe

cies

reco

rded

BAMGGOMSRS

Fig. 2. Sample-based species accumulation curve of the total number of ant species collected with arboreal, epigaeic andhypogaeic pitfall traps placed inTropical Dry Forest fragments and surrounding vegetation within different ecoregions (BA, MG,GO, MS and RS). Shaded area represents one standard deviation around mean values.



greater average distance from centroids betweenecoregions (0.586 � 0.0007) (F-value = 2.75, P =0.02,Table 2) than between TDF fragments (0.532 �0.002) (F-value = 2.05, P > 0.05, Table 2); that is, thefive Brazilian ecoregions were more variable than theTDF fragments. Furthermore, there was dissimilarityin species composition of ants between the fragments(TDF and surrounding vegetation) of each ecoregion(Permanova, P < 0.001, Table 2, Fig. 4), while thedispersion did not significantly differ (Permdisp,P > 0,05, Table 2).

Spatial partition

Partitioning of total species richness (g diversity)revealed that all observed diversity partitions are sig-nificantly different from those expected in a randomdistribution, except a-diversity (Table 3; Fig. 5 (Meanregion)). The contribution to total diversity increasedwith spatial scale, with variation among fragmentswithin an ecoregion (b1) and among ecoregions (b2)contributing to a combined 78%.

In the additive partitioning of diversity and nullmodels for each ecoregion individually (Table 3,Fig. 5 (Sites)), the observed alpha diversity was lowerthan expected from the null hypothesis in all ecore-gions (P > 0.05). Moreover, the observed b1 diversitybetween fragments (TDF and surrounding areas)from all ecoregions of Brazil was higher than expectedby the null hypothesis (P < 0.01), contributing to morethan 34% of regional diversity in each ecoregion.

DISCUSSION

Faunal composition

The ecoregion faunas showed remarkable composi-tional similarity at the genera level in terms of relativecontribution to species richness, despite the very lowproportion of shared species. Formicines (Campono-tus melanoticus) and myrmicines (Pheidole sp.3 andSolenopsis sp.2) were more common in all ecoregions,occurring in at least 10% of the pitfall traps. In fact,

Table 2. Pair-wise permutational tests of differences in position and dispersion of ant species communities sampled infragments (Tropical Dry Forest – TDF and surrounding vegetation) located in different ecoregions† of Brazil

FactorsPermanova Permdisp

r2 F-value

Among ecoregions Fragments 0.04**Ecoregion 0.10** 2.75*Fragments*Ecoregions 0.11**

Among TDFs Ecoregions 0.22** 2.05Among TDF and surrounding BA 0.10** 0.27

MG 0.22** 0.004GO 0.13** 1.55MS 0.08** 0.45RS 0.12** 0.07

Significant differences are in bold. *P < 0.05, **P < 0.001. †Ecoregions: MG, MS, GO, RS e BA.

Fig. 3. Ant species composition of Tropical Dry Forests located in different ecoregions of Brazil: BA (�), MG (�), GO (•),MS (�) and RS (�). Ordinations were plotted with non-metric multidimensional scaling (NMDS) based on the Jaccard distanceof the data (Stress = 0.09, P < 0.001).



some ant species sampled in this study, such as thosebelonging to Camponotus, Pheidole and Solenopsisgenera are considered ecologically dominant ants andcan influence the occurrence and distribution of lesscompetitive species (Dejean & Corbara 2003) in thefragments.This dominance could explain the observedspecies richness within fragments lower than thatexpected by chance. Species of these genera representmore than 37% of the fauna sampled in fragments.

There is wide variation in species compositionbetween fragments of the same ecoregion, around 75%of species are not shared between fragments.The habi-tats within each ecoregion present large differences inforest structure, floristic composition, microclimatesand soil types, which may differently influence thespecies composition of each fragment (Ribas et al.2003; Cabra-García et al. 2012; Schmidt et al. 2013).

Despite TDF fragments occurring in discontinuouspatches in the Brazilian biomes, these forests maintaintheir identities by preserving structural and functionalcharacteristics that favour the addition of speciesbelonging to these environments.

Ecological processes ¥ spatial scales

Additive diversity partitioning supports the argu-ment that lower a-diversity in tropical forests iscounterbalanced by higher b-diversity at larger spatialscales (Table 3; Hill & Hamer 2004). These resultshighlight the importance of considering each compo-nent of species richness at multiple spatial scales whencomparing habitats (Berry et al. 2008; Campos et al.2011; Paknia & Pfeiffer 2011; Woodcock et al. 2011).

Fig. 4. Composition of ant species of Tropical Dry Forests (�) and their surroundings (�) located in BA (A), MG (B), GO(C), MS (D) and RS (E) ecoregions. Ordinations were plotted with non-metric multidimensional scaling (NMDS) based on theJaccard distance of the data (P < 0.001).



At the regional scale our fundamental result is thatmore than 65% of total species richness of ants wasproduced by species turnover among ecoregions, indi-cating that the ecoregional scale plays a crucial role instructuring ant species composition in Brazil. Similarresults were detected for the ant community in Brazil-ian savannas (Campos et al. 2011) and in arid andsemi-arid areas in Iran (Paknia & Pfeiffer 2011). Thisresult is also consistent with the few comparable diver-sity partition studies that have been conducted withother taxonomic groups, such as Coleoptera andLepidoptera in deciduous forests (Gering et al. 2003;Summerville et al. 2003) and reef fish in Mexico(Rodriguez-Zaragoza et al. 2011).

The ecoregions in our study differ considerably inenvironmental conditions, vegetation structure andclimate history (Prado & Gibbs 1993; Olson et al.2001; Pennington et al. 2009; Werneck et al. 2011).Therefore, we suggest that ant communities werestructured by contingent history of the ecoregions,such as large-scale environmental changes that mayhave filtrated the species richness and compositionby promoting different migration, extinction andspeciation rates (Ricklefs 2006).

In addition, b-diversity among fragments was alsolarge and higher than expected by chance, indicat-ing this diversity component contributes to the over-all ant species richness in our studied ecoregions.

Table 3. Additive partitioning of total ant species richness into their alpha and beta components, using combined under-ground, ground and arboreal data

Diversity Diversity component Observed (% of total) Expected P

Mean region† a (within fragment) 34.9 (21.41) 41.73 NSb1 (among fragments) 20.7 (12.70) 13.87 <0.01b2 (among ecoregions) 107.4 (65.89) 96.06 <0.01g (total diversity) 163 151.66

EcoregionsBA a (within fragment) 35 (62.5) 41.32 NS

b1 (among fragments) 21 (37.5) 14.67 <0.01g (total diversity) 56 55.99

MG a (within fragment) 30 (61.22) 38.63 NSb1 (among fragments) 19 (38.77) 10.36 <0.01g (total diversity) 49 48.99

GO a (within fragment) 26.5 (61.63) 33.08 NSb1 (among fragments) 16.5 (38.37) 9.91 <0.01g (total diversity) 43 42.99

MS a (within fragment) 53 (63.09) 60.62 NSb1 (among fragments) 31 (36.90) 23.37 <0.01g (total diversity) 84 83.99

RS a (within fragment) 30 (65.21) 34.98 NSb1 (among fragments) 16 (34.78) 11.01 <0.01g (total diversity) 46 45.99

†Mean region – average among the five ecoregions of Brazil.The P-values were obtained by comparing the observed values ofeach diversity component with expected values generated through 1000 randomizations of the dataset.

Fig. 5. Additive diversity partitioning of ants among hierarchical spatial scales (fragments (Tropical Dry Forests and sur-rounding areas) and ecoregions of Brazil).The partition observed (Obs) was compared with expected values (Exp) calculated bythe null model for the average among the five ecoregions of Brazil (Mean) and for each ecoregion separately: BA (Site 1), MG(Site 2), GO (Site 3), MS (Site 4) and RS (Site 5). Asterisks indicate cases where the observed components of diversity differedfrom the expected (P < 0.05).



Furthermore, the ant species composition changesbetween patches of TDF and between TDF fragmentsand the surrounding vegetation in each ecoregion.Pleistocene climatic changes have been proposed as apossible force influencing the overall distribution ofTDF in the Neotropics (Prado & Gibbs 1993) and indriving evolution in TDF plants (Pennington et al.2000). Such evolutionary history is considered to be amajor driver of the local and regional diversity oflizards (Werneck & Colli 2006) and plant communities(Pennington et al. 2009) in Brazilian TDFs, and thisalso appears to be true for ants.

In addition to biogeographical context, phylogene-tic evidence suggests that TDF is a highly dispersal-limited system, showing high levels of b diversityamong the discontinuous TDF patches (Penningtonet al. 2009). We suggest that during historical events,populations of species of ants may have migratedamong TDF fragments (see Mayle 2004) through thedispersal corridor (Werneck et al. 2011) and afterthese areas were isolated, the ant community may havesuffered from external pressures of the biome in whichthey were embedded, leading to different evolutionaryhistories that consequently led to different diversityand species composition.

TDF conservation

Communities may seem to be more or less diversethan expected by chance, depending on the scale ofobservation. Conservation efforts should consider theimportance and magnitude of beta diversity at differ-ent spatial scales in proposing the creation of newprotected areas. Partitioning diversity can help in thisdetermination, assisting in the selection of areas whereecological processes determine a significantly higherdiversity than the random distribution of species. Fur-thermore, identifying the critical scale is crucial forpinpointing the appropriate spatial scale for habitatmanagement and ecological restoration.

Our results indicate that a substantial amount ofspecies richness is generated by beta diversity amongecoregions. This production of species richness isthe direct consequence of a restricted distribution ofseveral species within their ecoregions. As a result, toconserve the range of ant biodiversity all five ecore-gions need to be considered in conservation plans,such as the creation of new protected areas, especiallyif we consider ants a surrogate taxon that mirrors thepatterns in other plant and animal groups (Paknia &Pfeiffer 2011).

Species turnover among fragments within a givenecoregion contributes to the total diversity. Thisoutcome suggests that diversity partitioning shouldnot be restricted to a landscape scale and that it isimportant to consider regional subsets for further

investigation. The observed patterns among the fiveecoregions in our study indicate that different conser-vation strategies are needed for different ecoregions.For example, the depicted pattern in the MS ecoregionsuggests that single areas can represent much of antdiversity (51.5% of total diversity). On the other hand,the observed pattern in other ecoregions, such as GO(26.4% of total diversity), implies that conservationefforts should consider several fragments.

We conclude that this analysis helps to identifypossible non-random processes that govern diversity,despite the additive partitioning method only elucidat-ing the ecoregion diversity pattern at different spatialscales (Gering & Crist 2002). Thus, this techniquehelped us to identify the scale(s) where ecologicalprocesses contribute to the regional diversity of ants,and the scale that most contributes has become theprimary target for conservation efforts.

ACKNOWLEDGEMENTS

We thank the two anonymous reviewers for theirhelpful comments. To R. Solar for his suggestionson the initial drafts and A.S. Melo for his suggestionsand help in understanding the partition analyses.To R. Silvestre, M.M. Espírito-Santo, F.S. Neves, S.Lacau, P. Hermuche and F.S. Rocha for their logisticalsupport in collections from different regions of Brazil.To M.F. Demétrio, V. Carbonari, T.H. Auko, K.Dantas, L.B. Godinho, M.R. Silva and M.L. Oliveirafor their help in collecting the data. To the owner ofIndependência Farm, to S. Lacerda, to the IEF andthe SEMA in Rio Grande do Sul, for allowing thiswork in private and state parks. We thank R.S.M.Feitosa and V.E. Sandoval-Gómez for their help withant identification. This work received financial assist-ance from FAPEMIG. To CAPES and CNPq forgrants to the authors.

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SUPPORTING INFORMATION

Additional Supporting Information may be found inthe online version of this article at the publisher’sweb-site:

Appendix S1. Distribution of main biomes in Braziland Tropical Dry Forest (TDF) in particular, indicat-ing the study sites located in five ecoregions: BA (1),MG (2), GO (3), MS (4) and RS (5). Modified fromEspírito-Santo et al. (2009), with permission.Appendix S2. List of ant species sampled in TropicalDry Forest (TDF) and surrounding vegetations (SV)in five ecoregions in Brazil.



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Ant diversity partitioning across spatial scales: Ecological processes and implications for conserving Tropical Dry Forests