Genetic and morphological differentiation of the semiterrestrial crab Armases angustipes (Brachyura: Sesarmidae) along the Brazilian coast.
Natural populations have to cope with heterogeneous environments. In marine and estuarine habitats, this heterogeneity is related to biotic (food availability, predation, and interspecific and/or intraspecific competition) and abiotic (marine currents and temperature) forces that vary across temporal (from seconds to ages) and spatial (from meters to latitudes) scales. In response, individuals and populations can display variation in distinct aspects of their life histories, possibly reflected in genetic and morphological traits. This variation arises due to the different responses to local environmental pressure (via genetic frequencies or phenotypic processes) (Sotka, 2012). Such patterning of diversity can result in distinct local adaptation and structuring among populations along a geographic range.
Oceanic currents are one of the features of the world's marine environments with the most fundamental impact on animal movements and dispersal, especially for species with planktonic larval phases (Chapman et al., 2011). The coast of Brazil is influenced by different marine currents, such as the Central South Equatorial Current (CSEC) that splits into the North Brazil Current (NBC) and the South Brazil Current (SBC) (Fig. 1). The area of the current split varies annually, with a mean occurrence of between 10[degrees] S and 14[degrees] S near the surface (for more details, see Rodrigues et al., 2007). The CSEC split has been classified by some authors (Shanks, 2009: Weersing and Toonen, 2009) as a biogeographical barrier for species with planktonic larval phases. Based on the CSEC split, the Brazilian coast can be divided into three regions that are influenced by coastal currents: 1) north of the CSEC split; 2) the CSEC split region, between 10[degrees]-14[degrees] S; and 3) south of the CSEC split.
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Dispersal of marine organisms is recognized as a complex process, especially for marine invertebrates with larval phases (Fratini et al., 2011). The absence of evident physical barriers, combined with a reproductive strategy that results in thousands of larvae per spawn per female, large population sizes, and extensive larval phases potentially allow the dispersal of invertebrate larvae over wide distances, consequently reducing genetic variability among populations (Hedgecock, 1986; Avise, 2004; Fratini et al., 2011). Nevertheless, an increasing number of studies of marine animals with planktonic larvae show significant genetic differentiation over different geographic scales (e.g., Avise, 2004; Fratini et al., 2016).
The Brazilian coast extends over approximately 8500 km of shoreline and encompasses the third largest mangrove area in the world, accounting for 7% of global distribution. Mangroves in Brazil occur from the border with French Guiana almost to Laguna (Santa Catarina state) (4[degrees]30' N - 28[degrees]30' S), with an approximate surface cover of 25,000 [km.sup.2] of mangrove forests (Saenger et al., 1983; Schaeffer-Novelli et al., 2000). Larval dispersal can be a complex process for species thriving in estuarine habitats such as mangroves, marshes, and near polyhaline zones, since larvae released from the parental areas often must be flushed into the sea to undergo larval development in higher salinities, then return to estuarine areas to complete juvenile development (Bilton et al., 2002; Ituarte et al., 2012). Because estuarine environments are fragmented and patchy habitats, larval dispersal depends on the proximity between estuaries and the duration of the planktonic stages.
Ten species of fiddler crabs show intraspecific variation in carapace shape, among those populations distributed along the Brazilian coast (Hampton et al., 2014). On the other hand, the mangrove crab Ucides cordatus (Linneaus, 1763) shows no genetic variation in structure, implying high connectivity among populations separated by distances as great as 2700 km (Oliveira-Neto et al., 2007). The estuarine marsh crab Neohelice granulata (Dana, 1851) shows strong genetic differentiation
among populations in Argentina and Brazil, but does not exhibit a geographical pattern of morphological differentiation (Ituarte et al., 2012). These results suggest that there is no general pattern for potential differentiation in coastal crabs, and population variability within each species must be investigated separately.
Armases angustipes (Dana, 1852) is a semiterrestrial crab of the family Sesarmidae, and has a wide distribution. This species has been reported in Yucatan, Mexico; Andros Island, The Bahamas; Trinidad and Tobago; and Brazil (from the state of Maranhao to Santa Catarina) (Abele, 1992; de Melo, 1996). However, the presence of the morphologically very similar species Armases miersii (Rathbun, 1897) in the Caribbean makes the exact distribution and possible sympatry in Central America difficult to determine (Cuesta et al., 1999; Cuesta and Anger, 2001). Armases angustipes occurs in a large variety of habitats in coastal areas, such as sandy, muddy, and rocky margins of mangroves and adjacent areas, under dried leaves in border vegetation, in bromeliad leaf axils, and along the terrestrial margins of rocky shores. This species has four planktonic zoeal stages, all of which develop best in salinities greater than 20 psu, and one megalopa stage that returns to environments with lower salinity (< 32 psu) before metamorphosis to the first fully benthic juvenile stage (Anger et al., 1990; Cuesta and Anger, 2001). Thus, A. angustipes can be considered a species with an export larval strategy and, during its late development, a preference for estuarine systems.
In the larval export strategy, the zoeal larvae are released in estuarine areas. From there, they are transported to coastal or oceanic waters (higher salinity), where they pass through successive molts until the megalopa stage. This strategy facilitates dispersal and provides a more stable environment for larval development in the early larval stages (Anger, 2001; de Brito Simith et al, 2012).
To evaluate the population genetic and morphological structures of this semiterrestrial crab, and to test the influence of the Central South Equatorial Current (CSEC) as a geographic barrier to gene flow, we here present 1) haplotype data from the cytochrome c oxidase subunit 1 (Cox1) mitochondrial gene, 2) data on shape variation of the carapace and cheliped propodus, and 3) an evaluation of the correlation between the morphological and genetic distances from six populations along the Brazilian coast. The Cox 1 is a mitochondrial coding gene that has been used efficiently for evaluating population genetic structure in neotropical coastal decapods (Terossi and Mantelatto, 2012; Laurenzano et al., 2013; Thiercelin and Schubart, 2014). Both haplotype and shape variation data sets were used to determine the extent of gene flow and phenotypic variation among geographically separated populations. The combined data will help to understand the population biology and microevolution of this species and the connectivity between estuarine faunas in general. The data also may contribute to our understanding of the biogeography and intraspecific diversity of intertidal organisms and the connectivity among the patchily distributed faunas (Ragionieri et al., 2009; Laurenzano et al., 2013, 2016).
Materials and Methods
Sampling of Armases angustipes
Individuals of six Brazilian populations of Armases angustipes were sampled from Sao Luis do Maranhao ("Sao Luis"), Maranhao on 9 September 2014; Natal, Rio Grande do Norte on 28 August 2014; Maceio, Alagoas on 27 August 2014; Ilheus, Bahia on 23 August 2014; Aracruz, Espirito Santo on 20 August 2014; and Guaratuba, Parana on 7 December 2013 (Fig. 1) (Table 1). Samples were collected by hand and individuals were preserved in 75% ethanol.
Dorsal views of adult males yielded photographs of 63 carapaces (26 from Sao Luis, Maranhao (MA); 13 from Natal, Rio Grande do Norte (RN); 5 from Maceio, Alagoas (AL); 7 from Ilheus, Bahia (BA); 8 from Aracruz, Espirito Santo (ES); and 4 from Guaratuba, Parana (PR)) and 59 right cheliped propodi (24 from MA; 12 from RN; 4 from AL; 7 from BA; 8 from ES; and 4 from PR), using a Fujifilm Finepix HS10 camera (Fujifilm, Tokyo, Japan) with a resolution of 10 megapixels (Table 2). In general, studies of shape variance in crabs use a minimum number of 20 individuals per group or population studied (Silva et al., 2010; Wieman et al., 2014). However, some studies of less abundant species use a reduced number of individuals (<5) (Figueirido et al., 2012). Armases angustipes is less abundant than other coastal brachyuran species. Therefore, in some locations species abundance is naturally reduced. In the few studies, such as Cardini and Elton (2007), that have evaluated the effect of sample size and error on geometric morphometrics, the authors concluded that the mean size, standard deviation of size, and variance of shape were found to be fairly accurate, even in relatively small samples. Even if some populations in the present study have a relatively small number of individuals, the accuracy of the analyses is most likely not affected.
Differences in the number of sampled individuals and those that were used in the morphometric analyses are due to the fact that only intact carapaces and right chelipeds were used. In addition, females and juveniles were not included in the morphometric analyses because of sexual dimorphism and allometry that could have influenced the data. We considered only those individuals with carapace widths greater than 10 mm to be adults, based on a previous study by Kowalczuk and Masunari (2000). We defined 11 two-dimensional landmarks on the carapace and 8 landmarks on the propodus of the right cheliped (Fig. 2), using TPS Dig 2 software, ver. 2.16 (Rohlf, 2010). We performed a generalized Procrustes analysis (GPA) with raw landmark coordinates, which consisted of superimposition of the configurations through the centroid (i.e., the mass center of the configuration), scaling the centroid size of each configuration to a value of 1 and rotating (Monteiro and Reis, 1999). The GPA overlapping removes the effect of position, orientation, and size of the configurations of landmarks, and the aligned configurations then exclusively correspond to the shape of the structures (Adams et al., 2004). Because the carapace of A. angustipes is symmetrical, the shape elements can be separated into symmetrical and asymmetrical components (Klingenberg et al., 2002). Only symmetrical components of the carapace were used for analysis of shape variation. The size of each structure was estimated by the centroid size (root of the sum of the square distances of a group of points to that centroid) (Monteiro and Reis, 1999).
Size variation of the evaluated structures among the populations was examined by one-way analysis of variance (ANOVA), using the centroid size as the response variable and the populations as the predicting variable. Principal component analysis (PCA) was performed on the variance-covariance matrix of the GPA; the scores were used as new variables with a reduced dimensionality of the data (Klingenberg and Monteiro, 2005). These PCA scores (PCs) were used to test for variation of shape among each population by comparing three geographic groups: 1) Maranhao and Rio Grande do Norte populations (north of the Central South Equatorial Current split (CSEQ); 2) Alagoas and Bahia (CSEC split region between 10[degrees] and 14[degrees]); and 3) Espfrito Santo and Parana (south of the CSEC), using Multivariate Analysis of Variance (MANOVA). This grouping was based on prior expectations, considering the CSEC split as a possible barrier to larval dispersal. Shape differences between groups were evaluated using Canonical Variables Analysis (CVA). The relationship among the populations was visualized, and an unweighted pair group method with arithmetic mean (UPGMA) grouping analysis was carried out using the Mahalanobis distances corresponding to each analyzed structure (for more details, see Klingenberg and Monteiro, 2005). The influence of the habitat types on shape variation was evaluated by MANOVA. The habitats were divided into sandy and forest soil (organic rich) bottoms, based on the specificity of each environment (Table 1). Statistical analyses were performed with MorphoJ ver. 1,06d software (Klingenberg, 2011) and the R environment (R Development Core Team, 2011).
DNA extraction, amplification, and sequencing
A total of 66 individuals from 6 sample sites were used for genetic analyses. We included at least 10 or more representatives of each population in order to apply statistics to the population genetic analyses (Table 3). Mitochondrial DNA (mtDNA) was extracted from muscle tissue of pereiopods or chelae using the Puregene buffer system (Gentra Systems, Inc., Big Lake, MN). A 941-base pair (bp) region of the mitochondrial cytochrome c oxidase subunit 1 (Cox1) gene, encoding the 3' end, was amplified by means of polymerase chain reaction (PCR; 40 cycles: 45 s at 95 [degrees]C, 1 min at 48 [degrees]C, and 90 s at 72 [degrees]C (denaturing, annealing, and elongation temperatures, respectively)) in a 25-[micro]l volume with the primers COL8 5'-GAY CAA ATA CCT TTA TTT GT-3' and COH16 5'-CAT YWT TCT GCC ATT TTA GA-3' (Schubart, 2009). Amplification results were checked by running a 4-[MICRO]l PCR product on 1.5% TBE agarose gel electrophoresis. PCR products were sequenced in the forward direction with CoL8 (Macrogen Europe, Inc., Amsterdam, the Netherlands). Obtained sequences were proofread with Chromas Lite ver. 3.01 (2005, Technelysium Pty, Ltd., South Brisbane, Australia), adjusted manually when required, and then aligned with BioEdit ver. 7.2.5 (Hall, 1999). Sequences were submitted to GenBank under the reference numbers KX906606 to KX906671.
Genetic data analyses
To assess levels of genetic differentiation among populations, pairwise [[PHI].sub.ST] values (Weir and Cockerham, 1984; Loh et al., 2001) were calculated with Arlequin ver. 3.11 (Excoffier et al., 2005). The variance between tested groups was assessed by Analyses of Molecular Variance (AMOVA), using Arlequin ver. 3.11, comparing the same three geographic groups defined by marine currents as described for the morphometric analyses: 1) Maranhao and Rio Grande do Norte (north), 2) Alagoas and Bahia (CSEC split region), and 3) Espfrito Santo and Parana populations (south).
To examine the population history and to evaluate whether the populations followed the neutrality model at the sampling sites, Tajima's D, Fu's Fs, and Mismatch Distribution Analyses (Tajima, 1989; Fu, 1997; Schneider and Excoffier, 1999) were carried out using Arlequin ver. 3.11 software. DnaSp ver. 5.10.1 (Librado and Rozas, 2009) was used to assess nucleotide (7r) and haplotype (h) diversities. A statistical parsimony haplotype network (Polzin and Daneshmand, 2003) was constructed with PopART (Leigh and Bryant, 2015).
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The influence of genetic differentiation and geographic distance on body shape were tested with a three-way Mantel test, using the distance matrices of carapace and right cheliped propodus, genetic differentiation, and geographic distances among populations (Mantel and Valand, 1970). The morphometric matrices (carapace and cheliped propodus) were created using Mahalanobis distances, while the genetic matrix consisted of pairwise [[PHI].sub.ST] values and the geographic matrix consisted of the distances in km between populations. The Mantel tests were run using the vegan package in R (Oksanen et al., 2010; R Development Core Team, 2011).
The six analyzed populations of Armases angustipes did not differ significantly in mean centroid size of the carapace (F = 0.23, P = 0.94) or right cheliped propodus (F = 0.31, P = 0.89). Measurements ranged from 2.29 [+ or -] 0.57 cm to 2.56 [+ or -] 0.31 cm and 0.82 [+ or -] 0.29 cm to 1 [+ or -] 0.22 cm, respectively (Table 2).
Carapace shape differed significantly among populations of A. angustipes (Pillai's Trace = 1.87, P < 0.0001) (Table 4). The first canonical axis explained 50.81% of the variation among groups and was mainly related to the frontal region of the carapace, or landmark 1 (i.e., frontal end of the protogastric region), and landmarks 2 and 9 (frontal end of the anterolateral line) (Fig. 3). The majority of individuals of populations of northern and northeastern Brazil (Maranhao, Rio Grande do Norte, Alagoas, and Bahia) were found in the positive quadrant of shape space for the first canonical axis, and had a forward-projected carapace frontal region. In contrast, the majority of individuals from southern and southeastern Brazil (Espfrito Santo and Parana) showed negative scores for this axis and a receding carapace frontal region. The second canonical axis explained 31 % of the variation among groups and was mainly related to the cardiac line (Fig. 3). In the cluster analysis of carapace shape, the Parana population could be distinguished from all other populations (Espfrito Santo, Bahia, Alagoas, Rio Grande do Norte, and Maranhao) (Fig. 4A). High cophenetic correlation values were obtained (r = 0.89) in the carapace cluster analysis, indicating that the grouping satisfactorily reflected the structure of the morphometric data.
The right cheliped propodus shape also differed significantly among populations (Pillai's Trace = 2.39, P < 0.0001) (Table 5). The first canonical axis explained 41.96% of the data variation and was mainly related to landmarks 4, 5, and 6, corresponding to the predactylar lobe and the fixed finger area (Fig. 5). The Parana and Rio Grande do Norte populations showed negative scores for the first canonical axis, and had a receding fixed finger and predactylar lobe, unlike the other four populations (Espirito Santo, Bahia, Alagoas, and Maranhao). The second canonical axis explained 30.96% of the data variation and was mainly related to the upper portion of the cheliped (landmarks 1, 2, 3, and 4) (Fig. 5). In the cluster analysis of the shape of the right cheliped propodus, the result was similar to that of the carapace shape, with the Parana population being distinguishable from all other populations (Espirito Santo, Bahia, Alagoas, Rio Grande do Norte, and Maranhao) (Fig. 4B). High cophenetic correlation values were obtained again (r = 0.87), indicating that the grouping satisfactorily reflected the structure of the morphometric data.
There is evidence, based on the soil characteristics of each environment (sandy and organic rich soil), that habitat type influenced the shape of the carapace (f = 7.36, P < 0.001) and the right cheliped propodus (f= 7.56, P < 0.001).
A dataset of 66 mtDNA sequences with an alignment length of 941 base pairs (bp) was obtained from 6 Brazilian populations, resulting in 31 different haplotypes with 36 variable sites (Table 3). The highest number of haplotypes (h) within populations (n = 11) was observed in the Rio Grande do Norte population, and the lowest (n = 6) in the Alagoas and Parana populations.
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The haplotype network (Fig. 6) confirms the presence of five haplogroups (defined by the most common haplotypes: I, II, III, IV, and V). The highest haplotype diversity (Hd) was found in the northern populations of Maranhao and Rio Grande do Norte (0.933 and 1); the highest nucleotide diversity was seen in the northernmost population, Maranhao (0.00475). The lowest haplotype (0.758) and nucleotide (0.00147) diversities were found in the southernmost population, Parana (Table 3). Haplotype I was the most common haplotype and was recorded in over 37% of the analyzed individuals. It was found in all populations, while haplotype II was found in one individual of the Bahia, Espirito Santo, and Parana populations. Haplotype III was found in one individual of Maranhao, Rio Grande do Norte, Alagoas, and Espirito Santo, and two individuals from Parana; haplotype IV was found in two individuals from Maranhao and one from Bahia; and haplotype V was found in one individual from of Maranhao, Alagoas, and Espirito Santo.
The demographic history of Brazilian populations of Armases angustipes was reconstructed using mismatch distribution and neutrality tests. The mismatch distribution showed a bimodal distribution of pairwise differences (Fig. 7). The values of the neutrality tests (Table 3), when combining all populations (Tajima's D = -1.858, Fu's Fs = -24.07), were negative.
The mean pairwise [[PHI].sub.ST] values among populations were low (0.045) (Table 6). The majority of pairwise differences between populations were not significant, except for the comparison between Maranhao and Rio Grande do Norte, and between Maranhao and Parana, which were the two populations with the greatest distance between them (around 4100 km) (Table 6).
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The AMOVA results showed no significant differences between the three tested groups (P = 0.6). No significant differences were found within populations (P = 0.07), although the highest amount of variation (95%) was in this category. The variation among populations within groups was also not significant (P = 0.055), and was responsible for 7.41 % of the total variation (Table 6).
The Mantel tests revealed no significant correlation among morphological, genetic, or geographic distances for carapace (r = 0.29, P = 0.22) and right cheliped propodus (r = -.008, P = 0.49), validating the null hypothesis that the distance matrices were independent of each other (Table 7).
This study investigated the extent of gene flow and phenotypic variation among geographically separated populations of Armases angustipes. It also tested the influence of marine currents (i.e., Central South Equatorial Current (CSEC)) as a possible barrier for larval dispersal, using mtDNA sequence variation and anatomic landmarks to describe the shape of the carapace and cheliped propodus. Our results provide evidence of a high degree of genetic homogeneity among populations and significant shape variations over a wide geographic area in Brazil (around 4000 km), suggesting a high level of gene flow and confirming that the split of CSEC is not a barrier to larval dispersal in A. angustipes.
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The absence of a clear spatial genetic structure pattern, with shared haplotypes in populations separated by more than 4000 km and without significant [[PHI].sub.ST] values between the majority of populations, supports the hypothesis that this coastal marine species has high intraspecific connectivity. The same pattern was obtained for South American populations of the sesarmid tree-climbing crab Aratus pisonii (H. Milne Edwards, 1837) (Thiercelin, 2015) and for other estuarine crabs, such as Leptuca Uruguayensis (Nobili, 1901) (Laurenzano et al., 2012); Minuca rapax (Smith, 1870) (Laurenzano et al., 2013); Uca maracoani (Latreille, 1802) (Wieman et al., 2014); and Ucides cordatus (Linneaus, 1763) (Oliveira-Neto et al., 2007). This finding may be due to the extended planktonic larval phase that often results in a low level of genetic differentiation (Gooch, 1975; Crisp, 1978), or to movement along the coasts by adults.
Some authors, such as Neethling et al. (2008), have suggested that genetic connectivity increases with the larval dispersal ability of organisms. Because it is highly unlikely that adult sesarmid crabs disperse over long distances, the only possible dispersal option is by planktonic larvae, as observed for Uca annulipes (H. Milne Edwards, 1837) (now Austruca occidentalis (Naderloo, Schubart & Shih, 2016), see Shih et al., 2016) along the East African coast (Silva et al., 2010). Armases angustipes has an export larval strategy with long development (around 20 days) in the plankton, consisting of four zoeal stages, before the magalopae return to estuarine waters to complete development (Anger et al., 1990). This long period can help the species to disperse over great distances, forming a widespread metapopulation--at least for Brazilian populations--similar to what Fratini et al. (2011) assumed for the intertidal crab Pachygrapsus marmoratus (Fabricius, 1787) in the Mediterranean Sea.
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The AMOVA results also suggest that the CSEC split is not a strong barrier to larval dispersal in Armases angustipes. A similar pattern was observed for Brazilian populations of Uca maracoani (see Wieman et al., 2014). Populations south and north of the CSEC split seem to be able to exchange individuals between populations (shared haplotypes). The influence area, effective area, and speed of the CSEC can vary seasonally and over years (Rodrigues et al., 2007). Probably this temporal and seasonal variation enables gene flow among distant populations. Or the sharing of haplotypes is occurring among regional and "neighboring" populations, resulting in relative homogeneity among regional populations. The reproductive period, combined with the seasonality of the CSEC, can also influence gene flow. Ovigerous females are more abundant from January to July (De Araujo et al., 2014). The CSEC bifurcation reaches its southernmost position in July, increasing North Brazil Current transport, while the northernmost position is reached in November, increasing transport of the South Brazilian Current. In both cases, the seasonal variation is associated with changes in the local wind stress curl (Rodrigues et al., 2007). In this sense, it is likely that larval dispersal from south to north will be facilitated near July, while larval dispersal from north to south is facilitated near November. Thus, the probability of larval dispersal success varies seasonally.
The demographic history of Brazilian populations of A. angustipes indicates a recent population bottleneck, followed by demographic expansions, as denoted by Tajima's D and Fu's Fs negative values and the shape of the mismatch distribution. The high haplotype diversities and low nucleotide diversities are also a residual effect of a recent evolutionary history. Beyond this, individuals from all populations share the most common haplotype, which could also hint towards a recent bottleneck effect. Similar results were obtained for Brazilian populations of the mangrove-climbing crab Aratus pisonii (see Thiercelin, 2015) from the family Sesarmidae; the Ocypodidae Minuca rapax (see Laurenzano et al., 2013), Leptuca uruguayensis (see Laurenzano et al., 2012); and Uca maracoani (see Wieman et al., 2014).
The recent expansion events and possible bottleneck effect reflected by the significantly negative values of the neutrality tests (Tajima's D = -1.85, Fu's Fs = -24.07) can be related to recent geological and glaciation events. The closing of the Central American Isthmus (~3.5-2.8 Mya) affected ocean currents and sundered the range of marine species, severing their gene flow (Lessios, 2008). This event was observed for the sister species Aratus pisonii and Aratus pacificus Thiercelin & Schubart, 2014 in the Atlantic and Pacific Oceans, respectively. Beyond a restricted area of possible occurrence of tropical species due to the lower temperatures in northern South America, glaciation cycles caused a fluctuation in sea levels in the Atlantic subpolar region (~3.2-2.7 Mya). The Pleistocene glaciation cycles also affected the habitats and the evolution of tropical and shallow water marine organisms (Coates et al., 2004; Lessios, 2008). The northern part of the South American continent was affected by the Andean uplift, reorganizing the drainage systems of the continent, changing the outflows of the Orinoco and Amazon rivers, and increasing the amount of discharge waters (Hoorn et al., 1995, 2010). These events or the Pleistocene glaciations could have restricted the occurrence of Sesarmidae and other mangroverelated crabs to the Caribbean region. Then, once the temperatures increased this species possibly colonized South America in one or multiple events. But this assumption has not been tested, and further studies are necessary to support it.
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Although there is no clear genetic spatial structure, there was a tendency of higher haplotype and nucleotide diversities in northern populations of the present study (closer to the Caribbean region). This trend supports a possible lineage origin in northern South America or Central America, and can be related to historical geological and/or climatological events that influence the current species distribution from isolated populations of the Caribbean. In other crab species, expansion events have been correlated following changes in sea level and temperature during interglacial cycles (Favier Dubois and Scartascini, 2012; Ituarte et al., 2012). In the population genetic studies of Laurenzano et al. (2013, 2016) with Caribbean and mainland (South American) populations of Minuca rapax, the authors detected no differentiation among South American populations, but did so among Caribbean populations and between Caribbean and South American populations. Their findings suggest a genetic population structure with South American homogeneity and Caribbean heterogeneity.
In contrast to the genetic data, the six Brazilian populations of Armases angustipes exhibit significant intraspecific variation in shape, but not size, of the carapace and right cheliped propodus morphological spatial structure, especially for the carapace. A similar pattern of morphological population variation in shape for Brazilian populations was obtained for Uca maracoani (see Wieman et al., 2014) and for eight additional species of fiddler crabs (Hampton et al., 2014); for fiddler crabs of the Caribbean and eastern North America (Hopkins and Thurman, 2010); and for the sesarmid crab Perisesarma guttatum (A. Milne-Edwards, 1869) along the East African coast (Silva et al., 2010). We recognize a morphological population structure with three main groups: 1) Maranhao and Rio Grande do Norte, 2) Alagoas and Bahia, and (3) Espfrito Santo and Parana, based on the MANOVA result. Probably the main factors grouping the morphology of the populations are the similar selective pressures, such as environmental conditions, that are driving the phenotypic plasticity regionally in the same direction but diverging from each other. However, cluster analyses showed a distinct grouping. This analysis was based on the mean Mahalanobis distances among populations, while the MANOVA used the first and second PC scores to evaluate the differences among groups of populations. The three groups are morphologically distinct from each other, but some populations appear to have a closer morphological distance to populations belonging to other groups than to populations from the same group.
The most important morphometric differences observed concerned the frontal region of the carapace and the fixed finger area of the right cheliped propodus. The morphological variance among populations can be related to phenotypic plasticity driven by environmental differences between locations (Sanford and Kelly, 2011; Hampton et al., 2014).
Armases angustipes occurs in very different habitats in estuarine areas. These habitats have diverse physical, chemical (e.g., salinity, temperature, tidal regimes), and ecological (e.g., intra- and interspecific interactions, food availability) conditions throughout its geographical range. This amplitude of habitats may account for the local morphological divergence and phenotypic plasticity. In general, the sampled populations were from marginal regions of mangroves with varying substrate--sandy or organic rich soil. Representatives of the populations from Alagoas, Espirito Santo, and Maranhao occupy habitats with sandy bottoms, and all were grouped in the same branch of the cluster analysis. Individuals from Bahia and Rio Grande do Norte that occupy forest beyond mangrove areas with organic rich soil formed a sister branch in the cluster analyses of carapaces (Fig. 4A); in the MANOVA analysis, they showed morphological variance related to type of habitat. This morphological similarity among populations with similar types of substrate may reflect similar selective pressures (e.g., predators, food source and availability) that are influencing carapace shape. Phenotypic plasticity will be favored by local adaptations (Sotka, 2012).
When humidity is high, sandy bottoms are a more stressful environment to crab desiccation than those of forest soil. Hampton et al. (2014) showed that the intraspecific morphological variation found in eight species of fiddler crabs can be related to variation in humidity, to the relationship of humidity to water conservation in the crabs' gill chambers. The authors infer that differences in humidity can influence gene expression and morphological variation. The same pattern may be true for the species in the present study. But the factors driving the morphological variation in populations of Armases angustipes are currently unknown.
The southernmost studied population (from Parana) was also the most distinct in both carapace and cheliped analyses, and showed the largest morphological distances among populations (Tables 3, 4). This fact may be related to distinct physical conditions such as lower mean temperatures and higher mean annual rainfall, when compared to the other populations' locations (Alvares et al., 2014) or other ecological factors, as discussed above.
The differences in morphological similarity among populations when comparing carapace and right cheliped propodus are probably related to the plasticity of the shape of the carapace and cheliped propodus. In general, the carapace is considered a more conserved character than chelipeds in Brachyura (Harrison and Crespi, 1999). In this sense, the cheliped propodus is expected to exhibit a higher level of shape variation than the carapace, as a result of factors distinct from genetic sources. This theory is supported by the greater correlations--even if not statistically significant--between genetic and morphological distances based on the carapace than on the chelipeds (Table 7). In Brachyura, the size and shape of chelipeds are strongly influenced by sexual selection (especially in males), due to cohort behavior and male-male combat (Callander et al., 2013). Distinct population size or sexual proportion in a population may affect cheliped shape locally. Another factor affecting cheliped shape can be the prey and/or food type, quality, and availability (Smith and Palmer, 1994). Both hypotheses may affect cheliped shape in a short time period, reflecting a divergent morphological intraspecific variation when compared to other anatomical structures.
In the present study, there were no correlations between morphological versus genetic and geographic distances (Mantel test results). The incongruence of the genetic and morphological results suggests that processes responsible for the pattern of mtDNA are different, or act at different time scales from those impacting morphology. Contrasting patterns of morphological and genetic variation among populations are relatively common, and reflect the contrasting effects of gene flow and local adaptation. This incongruence was also observed for species of fiddler crabs and Neohelice granulata. from the South American coast (Ituarte et al., 2012; Hampton et al., 2014; Wieman et al., 2014).
This morphological and genetic incongruence can be derived from phenotypic plasticity, incomplete lineage sorting, or very recent and ongoing genetic divergence as well as environmental factors (as previously discussed) (Vogt et al., 2008; Sotka, 2012; Wieman et al., 2014). The most likely explanation for this incongruence is phenotypic plasticity (see also Schubart et al., 2010). In plasticity, different phenotypes can arise from the same genotype but be subjected to different environmental conditions. The large variety of biological factors that may affect the shape "operate" on a recent time scale. On the other hand, the genetic response to population separation acts on a larger time scale. Incomplete lineage sorting can occur when the effective population is large (probably not the case of A. angustipes), or the coalescence time of the genetic marker is not sufficient to observe variation on a certain scale (Wieman et al., 2014). In this sense, the morphological and genetic incongruence are probably related to the time required by the body shape and genetic markers to show intraspecific variation.
Our study revealed no clear correlation between morphological and genetic variation to ocean currents and geographic distances in Brazilian populations of Armases angustipes. We reject the hypothesis that the CSEC acts as a barrier to larval dispersal in this species. The considerable panmixia among populations from different estuaries with concurrent phenotypic divergence indicates that local populations are demographically interdependent, with larval exchange among adjacent estuaries. Our results also indicated that historical geological or climatological events as well as possible bottleneck effects may have influenced the present low genetic variability. The established morphological differentiation can be a plastic response driven by distinct environmental selective pressures, and not a direct cause of genetic differentiation. Future studies, using more sensitive markers such as microsatellites, may be useful in highlighting recent demographic dispersal events. The morphological and genetic data have provided complementary information about population variability for the studied species.
We are thankful to Dr. Nicolas Thiercelin for his introductions to genetic analyses to MZM. He and Salise Brandt Martins also helped during collecting. Thanks also go to the Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) for providing scholarships to MZM (process no. 141212/2013-6), and to the University of Regensburg, where Prof. Jiirgen Heinze provided additional support for laboratory supplies. Travel funds for C. D. Schubart and students to Brazil from 2013-2014 were facilitated by a PROBRAL exchange project (DAAD project ID 56266761) with Tania M. Costa. All biological samples collected for the present study complied with the current laws of the Brazilian Federal Government, and were conducted with the permission of the "Brazilian Institute of Environment and Renewable Natural Resources" (TBAMA) (Authorization # 42931-1-DIFAP/TBAMA, 11/05/2015).
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MURILO ZANETTI MAROCHI (1,*), SETUKO MASUNARI (1), AND CHRISTOPH D. SCHUBART (2)
(1) Departamento de Zoologia, Programa de Pos-Graduacao em Zoologia, Universidade Federal do Parana, 81531970 Curitiba, Brazil; (2) Zoology and Evolutionary Biology, University of Regensburg, 93040 Regensburg, Germany
Received 30 September 2016; Accepted 23 January 2017; Published online 5 April 2017.
(*) To whom correspondence should be addressed. E-mail: firstname.lastname@example.org
Abbreviations: AL, Maceio (city), Alagoas (state of Brazil); AMOVA, analysis of molecular variance; BA, Ilheus, Bahia (Brazil); Cox1, cytochrome c oxidase subunit 1; CSEC, Central South Equatorial Current; ES, Aracruz, Espfrito Santo (Brazil); GPA, generalized procrustes analysis; MA, Sao Luiz do Maranhao, Maranhao (Brazil); MANOVA, multivariate analysis of variance; NBC, North Brazil Current; PCA, principal component analysis; PR, Guaratuba, Parana (Brazil); RN, Natal, Rio Grande do Norte (Brazil); SBC, South Brazil Current; UPGMA, unweighted pair group method with arithmetic mean;
Table 1 Sampling locations, coordinates, numbers of individuals per sex, habitat descriptions, substrate types, and museum collection numbers of Armases angustipes at the Museu de Historia Natural do Capao da Imbuia (MHNCI), Curitiba, Parana, Brazil Location Coordinates M F Sao Luis, MA 2[degrees]28'26.3"S--44[degrees]12'54.5"W 42 13 Natal, RN 5[degrees]45'5.1"S--35[degrees]14'9.26"W 24 25 Maceio, AL 9[degrees]42'1.99"S--35[degrees]47'26.49"W 5 5 Ilheus, BA 14[degrees]40'28.9"S--39[degrees]4'49.3"W 16 Aracruz, ES 19[degrees]57'0"S--40[degrees]9'18.1"W 10 17 Guratuba, PR 25[degrees]51'41.2"S--48[degrees]35'23.5"W 7 8 Location Description of habitat Sao Luis, MA Between rocks, under marginal vegetation near mangrove areas Natal, RN Under leaves, marginal vegetation near mangrove areas Maceio, AL Under leaves, marginal vegetation near mangrove areas Ilheus, BA Under leaves, trunks between mangrove and Atlantic forest Aracruz, ES Under leaves and marginal vegetation near mangrove areas Guratuba, PR Under leaves, rocks, bromeliad leaf axils between mangrove areas and Atlantic Forest Location Substrate type Collection no. Sao Luis, MA Sandy soil C5413 Natal, RN Forest soil C5415 (organic rich) Maceio, AL Sandy soil C5414 Ilheus, BA Forest soil C5412 (organic rich) Aracruz, ES Sandy soil C5411 Guratuba, PR Forest soil C5160 (organic rich) AL, Alagoas; BA, Bahia; ES, Espirito Santo; MA, Maranhao; RN, Rio Grande do Norte; PR, Parana. Table 2 Mean centroid size of carapace and right cheliped propodus in cm ([+ or -] SD)from each population of male specimens of Armases angustipes Location Population Carapace (n) Mean [+ or -] SD Sao Luis MA 26 2.44 [+ or -] 0.37 Natal RN 13 2.47 [+ or -] 0.68 Maceio AL 5 2.37 [+ or -] 0.16 Ilheus BA 7 2.29 [+ or -] 0.57 Aracruz ES 8 2.47 [+ or -] 0.38 Guaratuba PR 4 2.56 [+ or -] 0.31 Location Cheliped propodus (n) Mean [+ or -] SD Sao Luis 24 0.91 [+ or -] 0.20 Natal 12 0.87 [+ or -] 0.37 Maceio 4 0.84 [+ or -] 0.11 Ilheus 7 0.82 [+ or -] 0.29 Aracruz 8 0.90 [+ or -] 0.17 Guaratuba 4 1 [+ or -] 0.22 AL, Alagoas; BA, Bahia; ES, Espirito Santo; MA, Maranhao; PR, Parana; RN, Rio Grande do Norte. Table 3 Genetic diversity indices and neutrality tests for each population of Armases angustipes based on a 941-base pair region of the Cox1 gene Location Population N h S Hd [pi] Sao Luis MA 10 7 10 0.933 0.00475 Natal RN 11 11 11 1 0.00213 Maceio AL 10 6 13 0.778 0.00409 Ilnus BA 11 8 16 0.891 0.00533 Aracruz ES 12 7 11 0.773 0.00253 Guaratuba PR 12 6 6 0.758 0.00147 MA + RN groups 21 16 20 0.971 0.00394 AL + BA groups 21 13 20 0.829 0.00464 ES + PR groups 24 10 14 0.746 0.00327 A. angustipes all sequences 66 31 36 0.86 0.00345 Location Population Tajima's D test Sao Luis MA 1.168 Natal RN -2.0111 ([dagger]) Maceio AL -0.7435 Ilnus BA -0.362 Aracruz ES -1.443 Guaratuba PR -1.167 MA + RN groups -1.265 AL + BA groups -0.8218 ES + PR groups -1.7562 (*) A. angustipes all sequences -1.858 ([dagger]) Location Population Fit's Fs, test Sao Luis MA -1.01 Natal RN -12.36 ([double dagger]) Maceio AL -0.228 Ilnus BA -1.451 Aracruz ES -2.026 Guaratuba PR -2.358 MA + RN groups -10.14 ([double dagger]) AL + BA groups -4.166 ES + PR groups -4.2080 ([dagger]) A. angustipes all sequences -24.07 ([double dagger]) (*) P < 0.05 ([dagger]) P<0.01 ([double dagger]) P < 0.001, except for Fu's Fs test. AL, Alagoas; BA, Bahia; ES, Espirito Santo; h, number of haplotypes; Hd, haplotype diversity; MA, Maranhao; A, number of individuals; RN, Rio Grande do Norte; PR, Parana; S, number of polymorphic sites; [pi], nucleotide diversity. Table 4 Morphological distances of the carapace MA RN AL BA ES PR MA < 0.0001 < 0.0001 < 0.0001 0.002 < 0.0001 RN 2.316 0.001 0.0206 < 0.0001 0.003 AL 2.591 2.985 0.0027 0.0019 0.0047 BA 3.717 2.316 4.047 0.0002 0.0025 ES 1.985 2.958 4.015 4.570 0.0016 PR 4.587 4.631 6.102 6.199 3.841 Source of variation Mahalanobis distance P-value Among north (MA, RN) x northeast (AL, BA) Populations 1.8899 0.0002 Among north (MA, RN) x south (ES, PR) populations 2.3804 < 0.0001 Among northeast (AL, BA) x south (ES, PR) populations 3.9858 < 0.0001 "Mahalanobis distance" (below diagonal) and corresponding P-values (above diagonal) refer to the pairwise carapace shape differences between the populations of Armases angustipes. The P-values were corrected for multiple comparisons by false discovery rates (Benjamini and Hochberg, 1995). AL, Alagoas; BA, Bahia; ES, Espirito Santo; MA, Maranhao; PR. Parana; RN, Rio Grande do Norte. Table 5 Mahalanobis distance of right cheliped propodus MA RN AL BA ES PR MA 0.001 0.001 < 0.001 0.001 0.001 RN 2.768 < 0.001 < 0.001 0.001 < 0.001 AL 3.772 4.817 0.003 0.005 0.015 BA 4.008 3.853 3.760 < 0.001 0.001 ES 2.479 3.502 3.909 4.543 0.002 PR 4.645 3.520 6.325 5.255 5.382 Source of variation Mahalanobis distance P-value Among north (MA. RN) x northeast (AL. BA) Populations 3.4310 < 0.0001 Among north (MA, RN) x south (ES, PR) populations 1.9039 0.0002 Among northeast (AL, BA) x south (ES, PR) populations 3.7398 < 0.0001 "Mahalanobis distance" (below diagonal) and corresponding P-values (above diagonal) refer to the pairwise right cheliped propodus shape distances between the populations of Armases angustipes. The P-values were corrected for multiple comparisons by false discovery rates (Benjamini and Hochberg, 1995). AL, Alagoas; BA, Bahia; ES, Espirito Santo; MA, Maranhao; PR. Parana; RN. Rio Grande do Norte. Table 6 Estimation of genetic pairwise differences of individual populations of Armases angustipes MA (10) RN (11) AL(10) BA (11) ES(12) PR (13) MA < 0.001 (*) 0.33 0.6445 0.1035 0.0068 ([dagger]) RN 0.23762 0.2285 0.163 0.1582 0.2207 AL 0.01527 0.0497 0.6884 0.7734 0.375 BA -0.05008 0.1117 -0.0538 0.3857 0.1464 ES 0.09841 0.0129 -0.0515 0.00038 0.6904 PR 0.21039 0.0104 0.02353 0.08203 -0.0095 Source of variation df Sum of squares Among groups 2 3.639 Among populations within groups 3 8.628 Within populations 60 93.158 Total 65 105.424 Fixation indices [F.sub.SC]: 0.0720 [F.sub.ST]: 0.0044 [F.sub.CT]: -0.0296 Source of variation Variance components Variation (%) P-value Among groups -0.0481 -2.97 0.6002 Among populations within groups 0.1204 7.41 0.0547 Within populations 1.5526 95.55 0.0703 Total 1.695 Fixation indices [F.sub.SC]: 0.0720 [F.sub.ST]: 0.0044 [F.sub.CT]: -0.0296 [[PHI].sub.ST] values are below diagonal; corresponding P-values are above diagonal. Permutations (n) =1023. Numerals in parentheses denote the sample size of each population. AL, Maceio Alagoas; BA, Ilheus; df, degrees of freedom; ES, Aracruz; MA, Sao Luis Maranhao; PR, Guaratuba Parana; RN, Natal Rio Grande do Norte; df, degrees of freedom; [F.sub.SC]: variance among populations within groups; [F.sub.ST]: variance among populations; [F.sub.CT]: variance among groups define a priori. (*)< 0.001 ([dagger]) P < 0.01 Table 7 Comparison of morphological, genetic, and geographic distances of populations of Armases angustipes using one-way and three-way-Mantel tests Comparison r-value P-value Simple Mantel test Carapace shape x geographic location 0.22 0.26 shape x genetic data -0.23 0.76 Right cheliped propodus shape x geographic location -0.001 0.48 shape x genetic data -0.16 0.71 Genetic data x geographic data -0.03 0.5 Three-wav Mantel test Carapace shape x genetic data x geographic location 0.29 0.22 Right cheliped propodus shape x genetic data x geographic location -0.008 0.49 r-value, correlation coefficient.
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|Author:||Marochi, Murilo Zanetti; Masunari, Setuko; Schubart, Christoph D.|
|Publication:||The Biological Bulletin|
|Date:||Feb 1, 2017|
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