DOI: 10.5061/dryad.zkh18938z
title: Rhizophora zonation, salinity, and nutrients in the western Atlantic

description: Rhizophora is the dominant genus of mangrove forests on the Atlantic coast
 of northern South America. What determines the zonation frequently
 observed in sympatric populations of the two neotropical species R.
 mangle, R. racemosa, and their hybrids, R. × harrisonii, is an open
 question. The most widely held hypothesis is that differences in salinity
 tolerance among the taxonomic groups explains the observed zonation. To
 address this question, we analyzed the elemental composition of soils and
 canopy leaves from 60 Rhizophora spp. trees distributed in different
 intertidal zones of an estuarine site of the Paria Gulf, Venezuela. The
 low intertidal zone showed lower salinity, organic matter, C, N, S, and
 Na, and higher bulk density, Al, Fe, and Mn concentrations compared with
 the higher intertidal zones. Using morphological characters and
 microsatellite molecular markers, we identified 39 pure R. mangle, 19
 hybrids, and only two pure R. racemosa. We found that both intertidal
 position and taxonomic groups explained most of the differences in leaf
 variables measured across trees. The ratio Mg/Ca, however, was higher in
 R. mangle than in R. racemosa and hybrids regardless of intertidal
 position. Moreover, at some specific intertidal position, R. mangle
 differed from R. racemosa and hybrids in the values of C, N, K, Mg, Fe,
 Mn, C/N, K/Ca, S/Ca, and d13C. We conclude that despite the scarcity of R.
 racemosa and the absence of a clear species zonation, our results suggest
 that R. mangle copes with salinity differently than R. racemosa and R. ×
 harrisonii.
description: The study site is located in an estuarine-riverine mangrove
 forest dominated by red (Rhizophora spp.) and black (Avicennia germinans)
 mangroves with few individuals of white mangrove (Laguncularia racemosa).
 The location of this mangrove forest is within the Paria gulf in a site
 known as Punta de Piedra (10.421767 N; 62.796708 W), bordering Turuépano
 National Park (Colonnello et al., 2009). Tidal channels such as Turuépano,
 La Palma, Guariquén, Guarapichito, and Ajíes surround this area. In
 addition, the San Juan River discharge is 25 km southeast of the site
 (Lasso et al., 2004), so freshwater and sediment discharge strongly
 influence the mangrove forest of the area.  The study
 site was selected based on its accessibility, density, and homogeneity of
 the vegetation, and relative protection from the Paria Gulf heavy winds.
 Based on information from the closest meteorological stations (i.e.,
 Caripito and Güiria), the area has a short dry season between February and
 March (Walter & Medina, 1971). However, data from a climate model
 covering a more extensive period (1982-2012) indicate a longer dry season
 from January to April, with averages of 1444 mm of precipitation and
 26.9ºC for temperature (Climate-Data.org, 2016). The river freshwater
 discharge and the effect of large tidal amplitudes (≈ 1 m, Herrera et al.,
 1981) compensate for the reduction in rainfall during the first quarter of
 the year. From June to December, rainfall exceeds 100 mm per month,
 contributing to significant leaching of salt from superficial soil layers.
 River discharge and rainfall maintains water salinity levels well below
 standard seawater (35‰) at the fringe of the mangrove-lined coast. For
 this study, we conducted fieldwork in December 2010 at the beginning of
 the dry season.  <em>Delimitation of the
 intertidal zones and sampling design</em> The
 tidal regime in the Paria Gulf is bi-diurnal and the tidal range varies
 between 1.8 and 3.2 m. Therefore, the penetration of tidal waters into the
 forest varies accordingly. In this study area, the maximum penetration
 inland of the mangrove forest is about 200 m. Beyond 200 m, non-halophytic
 species such as Symphonia globulifera and Cassipourea spp. (Colonnello et
 al. 2009) begin to appear. Based on this
 characterization of the study site, we established two transects
 perpendicular to the coast border toward the upper tidal zone and into the
 mangrove forest, separated 200 m from each other. On each transect, we
 delimited the two extremes of the intertidal range. The low intertidal
 zone (LI) was delimited as a 20m-wide stripe located at 2-20 m from the
 shoreline. Similarly, the upper intertidal zone (UI), was delimited as a
 20m-wide strip at 150-170 m from the shoreline. Finally, a 20m-wide strip
 at 90-110 m from the shoreline was considered to represent the middle
 intertidal zone (MI). This intermediate area helped us test for gradients
 of different parameters across the intertidal range. Thus, our sampling
 design included two plots in each of the three intertidal zones, one in
 each transect, totaling six plots. At the low
 intertidal zone (LI), each one of the two plots had an area of 900 m2 (30
 x 30 m) totaling 1,800 m2. Because of the density of Rhizophora spp. trees
 with DBH &gt; 5 cm increased from the shoreline (LI) toward the middle
 (MI) and upper (UI) intertidal zone, we reduced the size of the plots
 progressively. At the MI zone, each one of the two plots covered 400 m2
 (20 x 20 m), totaling 800 m2. At the UI zone, each one of the two plots
 covered 225 m2 (15 x 15 m), totaling 450 m2. 
 <em>Measurements of interstitial water
 salinity</em> We measured interstitial water
 salinity in situ at eight distances, along the two transects, from the
 coastal border toward the upper tidal zone into the mangrove forest,
 spanning the three intertidal zones. The distances were 2 and 20 m (at
 LI); 90, 100, and 110 m (at MI); and 150, 160, and 170 m (at UI). At each
 distance point, we collected porewater samples at 20, 40, and 80 cm depth
 with a 1 m long aluminum tube with perforations at the end, connected to a
 60-mL syringe. Salinity was measured with a digital refractometer
 (PAL-06S, Atago) and expressed in ‰. We used one or two replicates for
 each depth for a total of 72 measurements across the study
 site.   <em>​​​​​​​Sampling of soils and canopy
 leaves of Rhizophora spp. individuals</em> We
 randomly collected four soil samples at 0-20 cm depth of each plot for 24
 samples (i.e., four random samples x three intertidal zones x two plots
 per intertidal zone). We discarded one sample during processing. The
 remaining 23 samples were dried in the laboratory using a ventilated oven
 at 45oC to constant weight, ground, and then passed through a 20-mesh
 sieve. We separated each sample into two subsamples to measure the
 elemental composition (see section 2.5) and pH. For pH, the subsamples
 were hydrated with deionized water (1:5), homogenized manually for 5
 minutes, and allowed to rest for 14 h before measurements with a HANNA
 instrument (model 991301). Following the same sampling design, we measured
 bulk density in soil samples collected between 0-10 cm depth using PVC
 tubing (5 cm diameter, 10 cm length) for 24 samples. Samples were dried in
 the laboratory using a ventilated oven (45oC) until constant weight. This
 measurement was the quotient of soil dry mass/original volume of the PVC
 cylinder (200 cm3). Within each one of the six plots,
 we randomly selected ten trees of Rhizophora spp. with inflorescences
 totaling 60 individuals. Eight fully expanded green canopy leaves were
 collected from each of these trees for laboratory analysis of elements and
 isotopes (see sections 2.5 and 2.6).
 <em>​​​​​​​Elemental composition of canopy leaves and
 soils</em> Sixty samples of canopy leaves were
 oven-dried at 65oC, grounded and subsequently passed through an 18-mesh
 sieve. The powdered samples were ashed at 490oC and then dissolved in HCl
 6N.  Using the thermogravimeter (LECO TGA701), we measured dry mass
 (105oC) and ash content (490o).  In parallel, the 23 soil samples were
 digested sequentially in concentrated hot HNO3, H2O2, and HCl (Huang
 & Schulte, 1985). Then, using digested subsamples of both leaves
 and soil samples, Na, K, Mg, Ca, Fe, Mn, S, and P concentrations were
 measured using the Spectro Analytical Instruments GmbH (Boschstr. 10,
 47533 Kleve, Germany).  Additionally, total carbon and nitrogen were also
 measured using a macro dry combustion method with the Leco CNS- 2000
 Analyzer (Leco Corp. 3000 Lakeview Ave. St. Joseph, Michigan 49085,
 USA). <em>​​​​​​​Leaf isotopic C and N
 ratios</em> Isotopic C and N ratios of the leaves
 sampled were measured for each one of the 60 Rhizophora spp. trees at the
 L7 isotope laboratory of the University of Miami, Coral Gables
 (http://penguin.bio.miami.edu). Small tin spheres containing samples were
 placed in an automated elemental analyzer (Eurovector, Milan, Italy) and
 pyrolyzed. Gases from the pyrolysis were led into a mass spectrometer
 (Isoprime, Elementar) and analyzed for 13C and 15N abundance. Carbon and
 nitrogen isotope ratios are expressed as  d13C or  d15N =
 [(Rsample/Rstandard) -1] ·103. Rsample and Rstandard represent the molar
 ratio of the heavier (13C and 15N) to lighter isotope (12C and 14N) in the
 sample and standard, respectively. The standard for carbon isotope ratio
 was belemnite from the PeeDee formation in South Carolina, with an
 analytical precision of 0.1 ‰. The standard for the nitrogen isotope ratio
 was atmospheric nitrogen, with an analytical precision of 0.3 ‰.
 <em>​​​​​​​Mangrove species identification by morphological
 characteristics</em> In each of the six plots at
 three different intertidal zones, we identified mangrove trees
 of Rhizophora spp., Avicennia germinans, and Laguncularia racemosa.
 Identification of A. germinans and L. racemosa was straightforward because
 there are no other species of these genera in the area; however,
 identification of Rhizophora trees was complex. The only morphological
 character distinguishing the two species and the hybrids is the
 inflorescence type (i.e., the number of bifurcations in the
 inflorescence). Based on the inflorescence type, the 60
 sampled Rhizophora trees were identified as follows: those with 1-2
 bifurcations as R. mangle, those with 5-6-7 bifurcations as R. racemosa,
 and those with 3-4-5 bifurcations as hybrids, R. × harrisonii (Jiménez
 1987; Cerón-Souza et al., 2010). Due to the partly overlapping ranges of
 variation of inflorescence bifurcation in the three taxonomic units, which
 is associated to ongoing hybridization and introgression, field
 identification should ideally be corroborated genetically with molecular
 markers (Cerón-Souza et al., 2010; Cerón-Souza et al., 2014). 
 <em>​​​​​​​Genetic identification of sampled Rhizophora
 individuals</em> Of the 60 Rhizophora trees
 sampled, we genotyped 46 individuals to validate the taxonomic
 identification based on inflorescence type using DNA extracted from
 leaves. We used ten microsatellite loci (i.e., RM07, RM11, RM19, RM21,
 RM36, RM46, RM05, RM50, RM59, RS67) following the protocols in Cerón-Souza
 et al., (2010). The genetic composition of individuals and the hybrid
 class were determined using Bayesian genetic clustering analyses with
 Structure 2.3.3 (Falush et al., 2003, 2007; Pritchard et al., 2000) and
 NewHybrids 1.1 beta (Anderson & Thompson, 2002). In neither of the
 two analyses was the taxonomic identification based on inflorescence-types
 used as prior information. For Structure, an admixture model was assumed,
 with correlated allele frequencies and a uniform prior probability of K.
 We ran ten iterations for each number of groups assayed, from K = 1
 through K = 10, using 500,000 replicates of MCMC after a burn-in of length
 50,000 replicates. We applied the criterion of Evanno et al. (2005) to
 select the best estimate of the number of genetic groups based on DK
 calculation. For NewHybrids, we performed the analysis five times, each
 starting with a different random number of seeds and including 500,000
 iterations and 50,000 burn-in steps of the MCMC chain using a uniform
 allele and genetic frequency prior. Based on this approach, the 46
 individuals were assigned to one of six possible genotype classes: 1) pure
 R. mangle parent, 2) pure R. racemosa parent, 3) F1 hybrid (50 % of the
 genome originated from R. mangle and 50 % from R. racemosa), 4) F2 hybrid
 (50 % from F1 hybrid and 25 % from each of the parents R. mangle and R.
 racemosa), 5) backcrosses with R. mangle (50 % from F1 hybrid and 50 %
 from parent R. mangle), and 6) backcrosses with R. racemosa (50 % from F1
 hybrid and 50 % from parent R. racemosa).
 <em>​​​​​​​​​​​​​​Statistical analysis</em>
 To test differences in soil characteristics, we used a one-way
 ANOVA comparing LI, MI, HI intertidal zones. We also performed a principal
 component analysis of element concentration and element ratios to
 determine their correlation and characterize their spatial distribution
 across the intertidal zone. For the interstitial soil salinity, we used a
 two-way ANOVA to compare the effect of intertidal zone and
 depth. To test element concentrations, ratios of
 elements, and isotope differences across Rhizophora individuals, we
 performed a two-way ANOVA comparing the effect of the position in the
 intertidal zone and the taxonomic identification combining morphology and
 molecular markers.  In all analyses for both soils and
 leaves variables, we confirmed the homogeneity of variances (Bartlett
 test). For the few variables in which unequal variances were detected, we
 used Welch's test for means allowing for unequal standard deviations.
 We compared the means using the Tukey-Kramer HSD test at p&lt;0.05.
 For all statistical tests, we used JMP 13 (SAS Institute Inc.
 2016).