Living and dead Foraminifera as bioindicators in Saquarema Lagoon System, Brazil.
Transitional waters-bodies such as coastal lagoons with close connections to the sea are typically characterized by strong seasonal cycles resulting from periodical rainfall and wind-forcing events that affect the circulation and the residence time of water (Kjerfve, 1994; Prado et al, 2014).
In Brazil, the formation of coastal lagoons was associated with eustatic oscillation processes during the Quaternary (Knoppers et al., 1999) which can be observed at all shorelines, but mainly in Rio de Janeiro and the Rio Grande do Sul States (Esteves, 1998).
The Brazilian Saquarema Lagoon System (SLS) is connected with oceanic water through the Barra Franca Channel (Fig. 1), an artificial channel stabilized with engineering works in Saquarema Lagoon. A small portion of mangroves occurs in the northern margin of the Urusussanga and Jardim Lagoon (Belart et al., 2017; Dias et al., 2017). The Urussanga Lagoon, surrounded by swamps, receives the outflow of three rivers: Mato Grosso (or Rocandor), Tingui and Jundia. The Seco River drains in the Jardim and the Saquarema lagoons and receives the input of fresh water from the Padre and Bacaxa rivers (Moreira, 1989). In the region, the weather is warm and moist and characterized by rainy season in summer with annual precipitation between 1,000-1,500 mm (Barbiere & Coe-Neto, 1999).
The silting and organic matter accumulation generates high anthropic/natural impact in all Rio de Janeiro lagoons. These processes have accelerated in the last decades by deforestation, erosion related to agricultural activities and disordered population growth in most of the drainage basins. Some of the main impacts in this environment are impairment of water quality by effluent discharges without treatment, and changes in hydrologic balance in the last decades, assigned to engineering works such as the work to stabilize the communication channel with the ocean (Knoppers et al., 1999).
Coastal areas have traditionally been occupied by human civilization for the development of cities, industries and other activities promoting environmental stress (Agardy & Alder, 2005). The excessive discharges of nutrients from domestic and industrial effluents, combined with urban and agricultural runoff determine the enrichment of organic and inorganic nutrients in paralic ecosystems (Borja et al., 2012; Silva et al., 2013). These inputs intensify the eutrophication process, which is considered the main factor of stress in the coastal and marine environments (Meyer-Reil & Koster, 2000).
In the last decades, Foraminifera have been widely used as a proxy to describe coastal environments (Frontalini & Coccioni, 2007; Frontalini et al., 2009; Laut et al., 2011; Martins et al., 2013, 2015, 2016a, 2016b; Nesbitt et al., 2015). Foraminifera is commonly used as bioindicators because they have a short life cycle, which provides quick response to environmental changes, and are abundant, most diversified, with widespread distribution and specific ecological requirements (Murray, 2006; Laut et al., 2016a). The distribution of benthic foraminifera is controlled by many factors, such as temperature, salinity, dissolved oxygen, sediment grain size (Murray, 1991, 2001) and changes in the quality and amount of nutrients (Murray, 2006). Sediment characteristics strongly influence their distribution: they are more abundant in finer sediments but they are also influenced by sediment pollution (Bhalla & Nigam, 1986; Alve & Olsgard, 1999: Frontalini & Coccioni, 2007; Martins et al., 2013, 2015).
The knowledge about foraminiferal biodiversity in the Brazilian southeast coast was based on total assemblages (Vilela et al., 2003; Leipnitz et al., 2014; Clemente et al., 2015). These studies can lead to bias environmental interpretations because after death foraminiferal tests are exposed to taphonomic processes, such as transport, breaking and dissolving of carbonates.
The studies of Raposo et al. (2016) and Belart et al. (2017) were the only ones in Rio de Janeiro lagoons based exclusively on living assemblages. Both of them have considered a checklist of lagoonal foraminiferal species without an ecological approach. However, the number of living species was lower than that in total foraminiferal assemblages implying possible seasonal differences and/or the occurrence of allochthonous taxa which corroborates the hypothesis that the absence of a study that separates living individuals from the dead might lead to wrong environmental and paleoenvironmental interpretations.
The understanding of the differences between living (L) and dead (D) benthic foraminiferal assemblages and the factors that contribute to their distribution should be a key to accurate interpretations of paleoenvironmental changes (Goineau et al., 2015). The abundance and composition of L-assemblage vary over short time periods throughout the year in response to both specific-seasonal reproduction and environmental parameters (Murray, 1991). Population dynamics and dissimilarities of biological nature (differences in turnover rate and seasonal alterations in standing stock) can cause significant divergences between the L and D foraminifera (e.g., Jorissen & Wittling, 1999; De Stigter et al, 2007; Duros et al, 2014).
This study represents the first contribution to compare the L and D benthic foraminiferal assemblages and the sediment quality in the Saquarema Lagoon System (SLS) using biogeochemical proxies, as well as to predict how coastal ecosystems are responding to the combined effects of eutrophication and pollution pressure. Through these analyzes will allow recognizing the sectors where there is the highest preservation of foraminifera tests, thus delimiting priority areas for the paleoenvironmental studies.
MATERIALS AND METHODS
The Saquarema Lagoon System (SLS) is a tropical coastal ecosystem located in southeastern Brazil in the Rio de Janeiro State (22[degrees]55'-22[degrees]56'S, 42[degrees]35'-42[degrees]29'W). It has an area of 21.2 [km.sup.2], which extends approximately 11.8 km along the coast with an average depth of less than 2.0 m (Belart et al., 2017; Dias et al, 2017). This system is composed of four large connected lagoons (Fig. 1): Urussanga (12.6 [km.sup.2]), Jardim (2 [km.sup.2]), Boqueirao (0.6 [km.sup.2]) and Saquarema (6 [km.sup.2]).
This work is based on the analysis of sediment samples collected in 22 stations in SLS on March 2013 (Fig. 1), each sampled station was geo-referenced with a GPS (model GPSMAP[R] 78S). The methodology of sampling, data acquisition related to physical and chemical parameters (e.g., temperature, salinity, pH and dissolved oxygen (DO) content in surface water) and benthic foraminifera, as well as granulometric and geochemical data, such as total organic carbon (TOC), total sulfur (TS) and TOC/TS ratio are described by Dias et al. (2017).
Stained sediment samples were washed over sieves with mesh openings of 500 and 63 [micro]m. The residual fraction in each sieve was dried at 50[degrees]C, and the foraminiferal specimens were concentrated from the remaining sediment by flotation in trichloroethylene (Belart et al., 2017). All foraminiferal stained (living specimens) and unstained tests (dead specimens) were picked, identified, and counted under stereoscopic microscopic at 80x magnification. At least, 100 living (L) and 100 dead (D) individuals were counted per sample (Fatela & Taborda, 2002). The number of specimens found in the three replicates was therefore averaged. The generic taxonomical classification of Loeblich & Tappan (1988), and specific concepts of Boltovskoy et al. (1980), Debenay et al. (2002), and Martins & Gomes (2004) were followed. After identification, the names of species were checked using the World Register of Marine Species (WoRMS, 2014). Diversity was calculated using the Shannon index (H'), expressed by the formula: H' = [summation][p.sub.i]ln([p.sub.i]). The formula calculated the mean evenness (or homogeneity): J' = H' ln[(S).sup.-1], using the software MVSP.
Organic matter compounds
The total biopolymer concentration (BPC) consisting of lipids (LIP), proteins (PTN) and carbohydrates (CHO) were determined. These variables were analyzed in the sediment according to the methodology described by Dias et al. (2017) in the Laboratory of Palynofacies & Organic Facies of the Federal University of Rio de Janeiro (FURJ). The relative enrichment of biopolymers was evaluated through several parameters: PTN, CHO, LIP, BPC and PTN/CHO.
The maps shaped with ArcMap 10.5 and the Spline with Barriers (SWB) tool were configured with cell size 15 and 0 of a smooth factor, for this study in accordance to Dias et al. (2017). The interpolation shows the spatial distribution of the parameters concentration inside the lagoon and spatial distribution of ecological indexes and Foraminifera species. Coordinates are provided in WGS84.
Only samples with foraminiferal number >100 in L and D assemblages were considered for statistical analyses. Detrended Correspondence Analysis (DCA) was used to correlate the multiple environmental variables and their influence on ecological relationships and distribution of L and D assemblages. DCA analysis was performed in PCord 5.0 Software and based on the Relative Euclidean Distance for calculation of variance coefficient. DCA analysis was based on the relative abundance of L and D foraminifers' species (Appendix 1), as well as the physical and chemical parameters (pH, DO and salinity) and geochemical data such as BPC, CHO, LIP, PTN, TOC, and TS. Before the DCA analysis, these data were standardized to the square root of 0.5 to decrease the difference between the parameters scale.
Q-mode Cluster Analysis (CA) using the relative abundance of all species identified (Appendix 1) and based on the Euclidian Distance with Ward Linkage was applied to order the stations in groups with similar characteristics regarding L--and D-foraminifera. All data were normalized with the square root of 0.5 before the statistical analysis in PCord 5.0 software.
The water temperature showed small variations in the SLS. The highest and lowest temperature values (47.9 and 24.9[degrees]C) were recorded at stations SQ07, located near the mangrove fringe on the north bank of the Urussanga Lagoon, and SQ20 close to the communication channel between the Saquarema Lagoon and the Atlantic Ocean, respectively (Table 1).
The lowest and highest values of salinity (30.7 and 43.3) were measured at stations SQ08, in the Urussanga Lagoon, and SQ18, near Barra Franca Channel, respectively (Table 1). The highest pH value (8.7) was recorded in stations SQ02, SQ03 and SQ09 in the Urussanga Lagoon and the lowest (7.8) in SQ20 from the Saquarema Lagoon (Table 1). The maximum value of DO (8.3 mg [L.sup.-1]) was recorded in the SQ03 station from the Urussanga Lagoon and the minimum (5.5 mg [L.sup.-1]) in SQ10 station from the Jardim Lagoon (Table 1).
Grain-size and organic matter analysis
Clay fraction ranged from 16.1% to 44.95% in stations SQ09 and SQ07, respectively, and silt from 42.8% to 80.2% in stations SQ08 and SQ04, respectively (Table 1). The predominant grain size fraction in SLS surface sediments was silt, but in the stations located near the Barra Franca Channel and in SQ03 station located on the south bank of the Urussanga Lagoon sandy fractions dominated.
The minimum TOC recorded value was 0.09% in SQ22 station located in the communication channel with the Atlantic Ocean and maximum 21.5% in SQ10 station located on the Jardim Lagoon (Table 1). The highest value of TS (4.95%) was recorded in SQ08 station located on the northern bank of the Urussanga Lagoon, situated near the Mato Grosso River's mouth and the lowest in stations SQ20 and SQ21 (0.02%) from Saquarema Lagoon (Table 1). The ratio TOC:TS varied between 16.2 and 0.431 in stations SQ20 and SQ22, respectively.
The highest BPC content (32.96 mg C [g.sup.-1]) was found in SQ02 station located on the south bank of Urussanga Lagoon, and the lowest value was found in SQ22 (1.78 mg C [g.sup.-1]). The maximum PTN value was recorded in SQ10 station (4.64 mg C [g.sup.-1]) and the minimum in the SQ22 station (0.45 mg C [g.sup.-1]). The highest and the lowest average CHO content was recorded in the Boqueirao (21.7 mg C [g.sup.-1]) and the Saquarema Lagoon (14.4 mg C [g.sup.-1]), respectively. The highest average LIP content was found in the Jardim Lagoon (5.45 mg C [g.sup.-1]) followed by the Boqueirao Lagoon (4.48 mg C [g.sup.-1]). The lowest average value (3.02 mg C [g.sup.-1]) of LIP was found in the Saquarema Lagoon.
Living and dead foraminiferal assemblages
A total of 3,493 specimens belonging to 8 species and 3,430 specimens belonging to 9 species were picked and identified in the L and D assemblages, respectively (Fig. 2). The lowest L-foraminifera density (102 ind 50 [mL.sup.-1]) was found in SQ04. In the other stations, the L-foraminifer density ranged from 140 ind 50 [mL.sup.-1] in the inner portion of the Jardim Lagoon (SQ11) to 399 ind 50 [mL.sup.-1] in the Saquarema Lagoon (SQ20) (Fig. 2).
The D-foraminifera density ranged from 115 ind 50 [mL.sup.-1] in SQ04 to 338 ind 50 [mL.sup.-1] in SQ18 (Saquarema Lagoon). No L-foraminifera were found in SQ02, SQ03, SQ04, SQ05, SQ6, SQ07 and SQ22 (Fig. 2). In the stations SQ01, SQ03, SQ05, SQ06, SQ07, and SQ22 the D-foraminifera were absent.
For L-assemblages, the H' index values ranged from 0.2 to 1.4; the lowest and highest values were found in SQ08 at the Urussanga Lagoon and in SQ09 at the Jardim Lagoon, respectively. For D-assemblages, the H' index values varied between 0.6 and 1.6 in SQ08 (Urussanga Lagoon) and SQ12 (Jardin Lagoon), respectively (Fig. 2). The J' values varied between 0.2-0.9 and 0.6-0.9 for the L and D assemblages, respectively (Fig. 2).
The dominant families in both assemblages were Ammoniidae and Elphidiidae (Rotaliida Order, Rotalioidea Superfamily). Ammonia tepida and Ammonia parkinsoniana were the most abundant species throughout the lagoonal system, followed by Cribroelphidium excavatum both in L and D-assemblages (Fig. 3).
Ammonia tepida was present in L-assemblages in all stations (Fig. 3). The highest density of this species in L-assemblages was found along the Saquarema margin (48 ind 50 [mL.sup.-1] in SQ21 and 318 ind 50 [mL.sup.-1] in SQ20) and in the Urussanga Lagoon in station SQ08 (up to 165 ind 50 [mL.sup.-1]). In D-assemblages, A. tepida reached the highest densities in the Saquarema Lagoon (up to 173 ind 50 [mL.sup.-1]) and lowest values in the Urussanga Lagoon (1-21 ind 50 [mL.sup.-1]) (Fig. 3).
Ammonia parkinsoniana was found in all stations in both L and D-assemblages. The highest density values of A. parkinsoniana both in L and D-assemblages were identified in the northern margin of the Saquarema Lagoon (110 tests). In the northern part of the Urussanga Lagoon (SQ08), the density of A. parkinsoniana in L-assemblages reached 7 ind 50 [mL.sup.-1] to in D-assemblage to 134 ind 50 [mL.sup.-1]. Cribroelphidium excavatum was present along the Saquarema and Jardim lagoons in both L and D-assemblages (Fig. 3).
This species reached the highest density in L-assemblage, at station SQ21 (201 ind 50 [mL.sup.-1]) and in D-assemblage at station SQ13 (63 ind 50 [mL.sup.-1]). Cribroelphidium poeynum was found in the [L.sup.-1] assemblage only in SQ20 with low density (6 ind 50 [mL.sup.-1]) but in D-assemblage was distributed in Saquareama, Jardim, Boqueirao and Urussanga lagoons with a density ranging from 4-11 ind 50 [mL.sup.-1]. Elphidium gunteri (Elphidiidae Family) was restricted to the north margin in Saquarema, Boqueirao and Jardim lagoons with density values between 4-56 ind 50 [mL.sup.-1] (Fig. 4). Quinqueloculina seminula (Hauerinidae family) was found only in the Urussanga and Jardim lagoons both in L and D-assemblages (Fig. 4). The highest densities of Q. seminula in D-assemblage were reached in the Jardim Lagoon and the western part of the Urussanga Lagoon. Buliminella elegantissima (Buliminellidae family) was found only in D-assemblage at stations SQ10 and SQ15 in Jardim and Saquarema lagoons, respectively. A few agglutinated species (Order Lituolida) including Ammotium salsum (D-assemblages) Haplophragmoides wilberti (L-assemblages) and Trochamminita salsa (both L and D assemblages) were exclusively identified in the Urussanga Lagoon (SQ04).
The DCA analysis (Fig. 5) with 81% variance coefficient for the axis 1 and 14% for the axis 2 shows that the agglutinated species (A. salsum-D, H. Wilbert-L, and T. salsa-L and D) and Q. seminula (L and D) were related to higher values of TOC, TS, Temperature, PTN, DO and LIP values (axis 1). Ammonia tepida-D and A. parkinsoniana-L were associated with higher values of salinity, CHO, and sandy sediments, as well as, C. excavatum and C. gunteri (in axis 1). Elphidium poeyanum in both L- and D-assemblages was related to sand fraction, in axis 2. On the other hand, A. tepida-L and A. parkinsoniana-D were linked to axis 2 and the increase of clay fraction, TOC, TS, Temperature, PTN, DO and LIP (Fig. 5).
The Q-mode cluster analysis allowed the identification of five groups of stations in SLS considering 78% of similarity (Fig. 6). Group I is represented by stations SQ21-L and SQ21-D; Group II by stations SQ09-L, SQ09-D, SQ10-L, SQ12-L, SQ12-D, SQ13-L, SQ14L, SQ14-D, SQ15-L, SQ15-D, SQ19-L, SQ16-L and SQ18-L; Group III by stations SQ08-L, SQ08-D, SQ17-L, SQ20-L; Group IV by stations SQ11-L, SQ11-D, SQ13-D, SQ10-D, SQ16-D, SQ17-D, SQ18-D,SQ19-D, SQ20-D; and Group V by station SQ04-L and SQ04-D.
Bottom hydrodynamic and bathymetry of the SLS
Teodoro et al. (2010) suggested that the dominance of silty fractions indicates reduced velocities of bottom water currents as occurs in the SLS, except in the Saquarema Lagoon where sandy sediment and low values of TOC dominate (Dias et al., 2017). Thus the hydrodynamic regime seems to be more intense in the Saquarema Lagoon due to the proximity to the ocean connection through the Barra Franca Channel, strong tidal currents, and winds. On the other hand, the Urussanga Lagoon is considered the most confined region of the SLS, where the predominance of muddy sediments and high TOC content were founded.
According to Dias et al. (2017), sandy sediments are more common in shallow areas with depth less than 0.5 m. It was possible to identify an increase of this sediment fraction in much of the southern SLS margin at depths greater than 1 m. These sandy sediments might have been supplied by the wind, by removal, transportation, and deposition from the dunes fields.
The surface water physical and chemical variations were low in SLS during the sampling period except for the water temperature, and they were entirely different from those found by Lacerda & Goncalves (2001). The highest values of salinity found in the Saquarema Lagoon (station SQ18) are the consequence of sea water inflow and high evaporation rate. In this lagoon, powerful tidal currents associated with strong winds favor the accumulation sandy sediments in its central area (Dias et al., 2017). According to the Venice System, and considering the salinity variation (means of 33.3), the SLS can be considered a euryhaline environment (Smayda, 1983).
The temperature showed a direct relationship with the hydrodynamic and bathymetry of the lagoon since the shallower regions such as SQ07 (<30 cm) had the highest values but the average temperature found in SLS was in agreement with Bruno (2013). The DO values recorded in SLS were higher than that found in other Rio de Janeiro lagoons, such as the Marica Lagoon (Oliveira et al., 1955; Guerra et al., 2011) and the Araruama Lagoon (Debenay et al., 2001) in Araruama City. The range of the DO values indicates that the SLS is a favorable environment for the establishment of aerobic organisms of several trophic levels. These high values of DO can be favorited by the action of the wind in a shallow water body. The sediment had basic pH (7.8 to 8.7) in all the analyzed stations on the contrary to what has been recorded by Lacerda & Goncalves (2001).
Sedimentology and geochemistry
The highest average TOC content found in the Jardim Lagoon (9.53%) is related to the presence of peat in SQ10 station (Dias et al. 2017). According to Mendonca-Filho et al. (2003) sediments with TOC content >2.5% and high organic matter accumulation rate may be associated with dysoxic-anoxic conditions. In the SLS, the TS values ranged between 0.02-4.95 percent. Using the same methodology of analysis, Clemente et al. (2015) and Martins et al. (2015) recorded mean TS values of 1.4% in the Guanabara Bay (Rio de Janeiro) and 0.04% in the Bizerte Lagoon (Tunisia), respectively. Laut et al. (2016a) found values ranging between 0.04% and 1.73% in the Itaipu Lagoon (Rio de Janeiro). The TS in SLS was higher than those recorded in these areas but was lower than that found in the Santos Estuary (Sao Paulo), an area highly polluted from industrial and domestic sewage and where the average value was 6.03% (Siqueira et al., 2006).
The biopolymers content in marine and estuarine environments is used for the characterization and interpretation of the origin of organic matter accumulated in sediments (Silva et al., 2011). For instance, Cotano & Villate (2006) noticed that the organic matter provided by domestic liquid effluents and other anthropogenic activities could have high concentrations of PTN and LIP, whereas organic matter from a phytoplanktonic origin and vegetal detritus may have high CHO content. The highest carbohydrate value was found in the SQ02 station (25.9 mg C [g.sup.-1]), near the south margin of the Urussanga Lagoon that has a small mangrove swamp and in the center of all the lagoons of SLS (Dias et al., 2017). In lagoons suffering anthropic impacts, the increase of LIP concentrations may be associated with the increment of recalcitrant substances originated by fluvial inputs or sewage (Laut et al., 2016a). The highest concentrations of LIP were identified in the most urbanized margin of the Saquarema Lagoon (Dias et al., 2017). The PTN decomposition is faster than CHO, and, therefore, only new material, recently deposited, presents high PTN values (Fabiano et al., 1995; Laut et al., 2016a, 2017). However, in SLS, the high PTN values found in the north margin of the Jardim Lagoon (Dias et al., 2017) suggest a natural source from mangrove and peat region.
Characterization of living foraminiferal assemblages
Foraminiferal richness commonly documented for coastal lagoons vary, in general, between twenty and thirty species (Fatela & Taborda, 2002; Laut et al., 2007), much higher than that found in the SLS. The species richness identified in L-assemblages of the SLS was lower than recorded in other lagoons of southeastern Brazil. For instance, Vilela et al. (2011) recognized 52 foraminiferal species in the Rodrigo de Freitas Lagoon; Bomfim et al. (2010) identified 22 species in the Marica Lagoon and; Debenay et al. (2001) found of 74 species in the Araruama Lagoon. However, these studies were based on the total assemblage, which may incorporate allochthonous species. The low richness of L-assemblages might also be a consequence of periodic variations due to the seasonal reproduction of the species and differential life cycles.
Their geographical position may explain the higher richness and density values of L-assemblages in stations SQ19 and SQ20. These stations were located close to the Barra Franca Channel that promotes the greater exchange of marine water and high-quality food supplied from the ocean. The relatively low foraminiferal H' diversity found in the SLS can be compared to other Brazilian coastal regions, such as the Rodrigo de Freitas Lagoon (Vilela et al., 2011) and the Marica Lagoon (Bomfim et al., 2010) that ranged from 0.88 to 2.5, respectively. In these studies were however analyzed only total assemblages (living+dead). Martins et al. (2016a) and Delavy et al. (2016) using living foraminifera reported diversity values between 0.75 and 1.7 in the inner area of the Guanabara Bay. The values at SLS can be attributed to several factors including the untreated domestic sewage input and the long residence time (or renewal) of water. According to Alves (2003), the water residence time can reach up 58 days in the Urussanga Lagoon and 20 days in the Saquarema Lagoon. The SLS long water residence time, even for the Saquarema Lagoon that is directly connected with the ocean, suggests that the artificial Barra Franca Channel may not be sufficient for water renewal in SLS required for the establishment of large diversified foraminiferal assemblages.
In the SLS, changes in the composition of the L-assemblages, from predominantly calcareous species close to sea channel to an increase of agglutinated species in confined regions, can be observed. Haplophragmoides wilberti and T. salsa in the L-assemblages were restricted to the most confined areas in the Boqueirao Lagoon (SQ04). These dominant species, as suggested by several authors, is very resistant to salinity changes and reported as dominant in transitional environments such as coastal lagoons (Laut et al, 2012, 2016a, 2017; Martins et al, 2015).
According to Hayward et al. (1996), C. excavatum is distributed preferably in coastal environments, where conditions of high salinity, nitrogen, and phosphate prevail. This species is also considered bioindicators of eurytopic conditions by several authors because of their ability to live in a wide variety of habitats and to tolerate a wide range of environmental conditions. It has been recorded in several lagoons of Brazil and around the world (Debenay et al., 2002; Vilela et al., 2003; Laut et al, 2012; Martins et al, 2015; Belart et al, 2017). Cribroelphidium excavatum is also common in estuarine systems like Potengi River in northeastern of Brazil (Souza et al., 2010) and Paraiba do Sul River, Rio de Janeiro State (Laut et al., 2011).
Ammonia parkinsoniana was reported as a dominant species in the total foraminifera assemblages (living+dead) in several lagoons of Rio de Janeiro: the Marica Lagoon (Bomfim et al., 2010), the Rodrigo de Freitas Lagoon (Vilela et al., 2011) and the Araruama Lagoon (Debenay et al., 2001). This species shows eurytopic behaviors because it was reported in others coastal lagoons with very distinct environmental conditions, such as the Bizerte Lagoon (Tunisia) and associated to the significant and sustainable flux of high-quality nutrients (Martins et al., 2015). In the SLS, A. parkinsoniana was found in almost all stations, but reached the highest abundance at stations close to the connection with the ocean, under the higher marine influence related to physical and chemical parameters and food quality.
In addition to A. parkinsoniana, the DCA also suggests other bioindicators of higher marine influence: C. excavatum, C. poeyanum, and E. gunteri (Fig. 5). These species are the most spatially represented in the lagoon system. However, their abundance increased under relatively low temperatures, TOC, PTN and LIP values and relatively high salinities and CHO. These species also have a eurytopic behavior since several authors have also reported them in the world (Frontalini et al, 2009, 2010, 2013; Laut et al. 2016a; Martins et al. 2016a, 2016b).
The DCA results also point out that A. tepida is related to confined areas and regions with higher temperature, TOC, PTN and LIP but to relatively low BPC content. The results confirmed the adaptive behavior of this species that was present in Lassemblage of all the analyzed stations, in different values of salinities, temperatures, and pH. Ammonia tepida is commonly founded in transitional environments under pollution stress from natural or anthropogenic sources (Laut et al., 2016a; Martins et al., 2016a, 2016b). This species was also found in other lagoons in Italy, such as Orbetello Lagoon (Tuscany, the coast of Tyrrhenian Sea), Lake Varano (Southern Italy), and the Santa Gilla Lagoon (Cagliari) related to the most confined areas (Frontalini et al., 2009). The proliferation of this species in coastal environments is favored by the reduced competition in hypo- and hypersaline environments since it is a euryhaline species (Murray, 1991).
Species belonging to Miliolida Order are stenohaline and have low resistance to low concentrations of oxygen (Todd & Bronnimann, 1957). However, Q. seminula can be considered characteristic of mixohaline and brackish environments (Ruiz et al., 2005; Laut et al., 2014). In some tropical ecosystems like SLS, this species is associated with sediment of high organic matter and water with high dissolved oxygen level (Clemente et al., 2015; Laut et al., 2016a; Martins et al., 2016a).
Comparison between living and dead foraminiferal assemblages
The distribution of L and D assemblages was significantly different. These differences may be related to the hydrodynamic conditions or seasonal variations in the community structure in SLS. The analysis of data suggests that the Jardim Lagoon was the depocenter of empty foraminiferal tests. In this lagoon, the density and richness of L-assemblage were higher in the southern margin, and the D-assemblage was higher in the northern. The exception was the station SQ12 in the south of the Jardim Lagoon where the ecological indexes were similar between L and D assemblages.
The species A. parkinsoniana, A. tepida and C. excavatum are the most representative species in the region because they are distributed along to SLS in D and L assemblages. However, A. tepida and A. parkinsoniana would be used with care as bioindicators in paleoenvironmental studies at SLS because in DCA they present opposite position between L and D. The opposite distribution in the DCA might suggest post-mortem transport effect. Ammonia tepida was transported from the most confined to the marine influence area, and A. parkinsoniana followed the opposite direction.
The agglutinant species H. wilberti (L), T. salsa (L and D) and the calcareous Q. seminula (L and D) are the bioindicators of low-energy regions in SLS because responded positively in the DCA to higher TOC, TS, temperature, PTN and DO values. These species are commonly found in the inner portion of bays (Phleger, 1957), lagoons (Bomfim et al., 2010; Debenay et al., 2001) and mangroves (Debenay et al., 2004; Woodroffe et al., 2005). Some authors like Donnici et al. (2012) and Debenay et al., (2015) reported that miliolids as Q. seminula were favored by environments with greater hydrodynamics and oxygenated waters, which did not occur in the SLS. These species were found in confined regions in L and D. Haplophragmoides wilberti might not be useful as a bioindicator of confined areas for paleoenvironmental studies at SLS. This species was not found in Dassemblage, and this suggests the action of taphonomic processes. In the other hands, the bioindicators of high hydrodynamic were E. poeyanum and C. gunteri that are associated in DCA to sand and CHO in L and D-assemblages.
The cluster analysis identified regions in SLS showing the most substantial difference between L and D assemblages. The most significant differences can be observed between Group II (mostly composed by L-assemblage), Group III (only composed by L-assemblage) and Group IV (mostly composed by D-assemblage). The distribution of these groups was in the central region of the Saquarema Lagoon (SQ16, SQ17, SQ18, SQ19, and SQ20), the Boqueirao Lagoon (SQ13) and north of the Jardim Lagoon (SQ10). The exceptions were the stations SQ09, SQ12, SQ14, SQ15 (Group II) and SQ11 (Group IV) that were represented both in L and D assemblages in the same groups.
The high similarity (78%) occurred with the stations SQ04 and SQ21 that formed isolated groups in the dendrogram. Thus, only a few regions in the SLS presented the preservation of biocenosis (L-assemblage) as indicated in Figure 6. These regions should be prioritized in paleoenvironmental studies because the thanatocoenosis (D-assemblage) shares great similarity with biocenosis. The results indicated that environmental studies based on total assemblage are not recommended in the SLS because the taphonomic processes are very active.
The SLS, a transitional environment, was characterized and TOC, biopolymers, grain-size, and DO were identified as the main factors responsible for the distribution of foraminiferal assemblage. The high values of TOC and TS suggest that this environment has suffered natural and anthropogenic pressures. The high values of biopolymers indicate a very impacted environment with long water residence time. The species richness in L-assemblages was very low compared to other Brazilian coastal regions and dominated by species with eurytopic behavior such as A. tepida, A. parkinsoniana, and C. excavatum. The species H. wilberti was only recognized in L-assemblages next the mangrove fringe, whereas B. elegantissima and A. salsum were solely identified in the D-assemblage. These differences between L and D-assemblage indicate transport, dissolution, and seasonality in the system. The composition of assemblages in the SLS reflected the reduction of marine gradient influence. The agglutinated species and Q. seminula were bioindicators of most confined areas, and A. parkinsoniana, C. excavatum, C. poeyanum, and E. gunteri characterized the most marine influenced areas. The species A. tepida and A. parkinsoniana cannot be considered as bioindicators of hydrodynamic in paleoenvironmental studies in the SLS as both were transported after death. The cluster analysis showed that only a few regions in each lagoon present right conditions of preservation of biocenosis. The results of this analysis indicated the best regions for the application of paleoenvironmental studies and that the studies with total assemblages do not represent the biotic conditions in the SLS.
This research was supported by National Council of Technological and Scientific Development--CNPq (Universal 445830/2014-0) and Fundacao de Amparo a Pesquisa do Estado do Rio de Janeiro FAPERJ (Biota RJ E26/11.399/2012). The authors would like to thank Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior--Brasil CAPES (Finance Code 001) for the Master Fellowship of Pierre Belart, Gabriel Panigai and Debora Raposo. To CNPq and UNIRIO for the fellowships from Scientific Undergra-duate Program of Renan Habib and Eduardo Volino. This paper is a contribution of the National Institutes for Science and Technology in Ecology, Evolution and Conservation of Biodiversity (INCT EECBio) ant the Brazilian Network on Global Climate Change Research (Rede CLIMA).
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Received: 26 October 2017; Accepted: 13 July 2018
Appendix 1. Abundance and ecological index of foraminifera from Saquarema Lagoon System (L: represent the living assemblage, and D: dead assemblage). Ammonia Ammonia Ammotium Buliminella parkinsoniana tepida salsum elegantissima SQ01_D 0 0 0 0 SQ01_L 0 1 0 0 SQ02_D 0 0 0 0 SQ02_L 0 0 0 0 SQ03_D 0 0 0 0 SQ03_L 0 0 0 0 SQ04_D 0 3 27 0 SQ04_L 0 0 0 0 SQ05_D 0 0 0 0 SQ05_L 0 0 0 0 SQ06_D 0 0 0 0 SQ06_L 0 0 0 0 SQ07_D 0 0 0 0 SQ07_L 0 0 0 0 SQ08_D 21 134 0 0 SQ08_L 7 165 0 0 SQ09_D 44 70 0 0 SQ09_L 22 65 0 0 SQ10_D 110 38 0 2 SQ10_L 37 72 0 0 SQ11_D 109 12 0 0 SQ11_L 44 28 0 0 SQ12_D 19 55 11 0 SQ12_L 84 156 0 0 SQ13_D 145 54 0 0 SQ13_L 54 145 0 0 SQ14_D 82 102 4 0 SQ14-L 102 82 0 0 SQ15_D 82 173 0 1 SQ15_L 33 84 0 0 SQ16_D 160 84 0 0 SQ16_L 84 160 0 0 SQ17_D 130 66 0 0 SQ17_L 17 118 0 0 SQ18_D 270 25 0 0 SQ18_L 36 83 0 0 SQ19_D 173 110 0 0 SQ19_L 110 173 0 0 SQ20_D 82 38 0 0 SQ20_L 47 318 0 0 SQ21_D 40 36 0 0 SQ21_L 76 48 0 0 SQ22_D 0 0 0 0 SQ22_L 0 0 0 0 Cribroelphidium Cribroelphidium Elphidium excavatum poeyanum gunteri SQ01_D 0 0 0 SQ01_L 0 0 0 SQ02_D 0 0 0 SQ02_L 0 0 0 SQ03_D 0 0 0 SQ03_L 0 0 0 SQ04_D 0 0 0 SQ04_L 0 0 0 SQ05_D 0 0 0 SQ05_L 0 0 0 SQ06_D 0 0 0 SQ06_L 0 0 0 SQ07_D 0 0 0 SQ07_L 0 0 0 SQ08_D 0 8 0 SQ08_L 0 0 0 SQ09_D 0 0 0 SQ09_L 23 0 7 SQ10_D 56 7 23 SQ10_L 30 0 0 SQ11_D 23 11 56 SQ11_L 12 0 56 SQ12_D 33 0 12 SQ12_L 59 0 23 SQ13_D 63 8 37 SQ13_L 63 0 37 SQ14_D 62 0 11 SQ14-L 62 0 11 SQ15_D 38 0 21 SQ15_L 82 0 11 SQ16_D 58 0 32 SQ16_L 58 0 32 SQ17_D 40 0 15 SQ17_L 14 0 15 SQ18_D 29 4 10 SQ18_L 22 0 16 SQ19_D 48 0 4 SQ19_L 48 0 4 SQ20_D 29 0 13 SQ20_L 23 2 9 SQ21_D 58 0 13 SQ21_L 201 0 21 SQ22_D 0 0 0 SQ22_L 0 0 0 Haplophragmoides Quinqueloculina Trochamminita wilberti seminula salsa SQ01_D 0 0 0 SQ01_L 6 6 7 SQ02_D 0 0 0 SQ02_L 0 0 0 SQ03_D 0 0 0 SQ03_L 0 0 0 SQ04_D 0 33 2 SQ04_L 0 0 0 SQ05_D 0 0 0 SQ05_L 0 0 0 SQ06_D 0 0 0 SQ06_L 0 0 0 SQ07_D 0 0 0 SQ07_L 0 0 0 SQ08_D 0 0 0 SQ08_L 0 0 0 SQ09_D 0 17 0 SQ09_L 0 38 0 SQ10_D 0 11 0 SQ10_L 0 44 0 SQ11_D 0 21 0 SQ11_L 0 0 0 SQ12_D 0 11 0 SQ12_L 0 0 0 SQ13_D 0 0 0 SQ13_L 0 0 0 SQ14_D 0 0 0 SQ14-L 0 0 0 SQ15_D 0 0 0 SQ15_L 0 0 0 SQ16_D 0 0 0 SQ16_L 0 0 0 SQ17_D 0 1 0 SQ17_L 0 0 0 SQ18_D 0 0 0 SQ18_L 0 0 0 SQ19_D 0 0 0 SQ19_L 0 0 0 SQ20_D 0 0 0 SQ20_L 0 0 0 SQ21_D 0 0 0 SQ21_L 0 0 0 SQ22_D 0 0 0 SQ22_L 0 0 0 Appendix 2. Absolute abundance of foraminifera from Saquarema Lagoon System (L: represent the living assemblage, and D: dead assemblage). Ammonia Ammonia Ammotium Buliminella parkinsoniana tepida salsum elegantissima SQ01_L 0 1 0 0 SQ04_D 0 3 27 0 SQ08_D 134 21 0 0 SQ08_L 7 165 0 0 SQ09_D 70 44 0 0 SQ09_L 22 65 0 0 SQ10_D 38 110 0 2 SQ10_L 37 72 0 0 SQ11_D 12 109 0 0 SQ11_L 44 28 0 0 SQ12_D 55 19 11 0 SQ12_L 84 156 0 0 SQ13_D 54 145 0 0 SQ13_L 54 145 0 0 SQ14_D 102 82 4 0 SQ14-L 102 82 0 0 SQ15_D 173 82 0 1 SQ15_L 33 84 0 0 SQ16_D 84 160 0 0 SQ16_L 84 160 0 0 SQ17_D 66 130 0 0 SQ17_L 17 118 0 0 SQ18_D 25 270 0 0 SQ18_L 36 83 0 0 SQ19_D 110 173 0 0 SQ19_L 110 173 0 0 SQ20_D 38 82 0 0 SQ20_L 47 318 0 0 SQ21_D 36 40 0 0 SQ21_L 76 48 0 0 Cribroelphidium Cribroelphidium Elphidium excavatum poeyanum gunteri SQ01_L 0 0 0 SQ04_D 0 0 0 SQ08_D 0 8 0 SQ08_L 0 0 0 SQ09_D 0 0 0 SQ09_L 23 0 7 SQ10_D 56 7 23 SQ10_L 30 0 0 SQ11_D 23 11 56 SQ11_L 12 0 56 SQ12_D 33 0 12 SQ12_L 59 0 23 SQ13_D 63 8 37 SQ13_L 63 0 37 SQ14_D 62 0 11 SQ14-L 62 0 11 SQ15_D 38 0 21 SQ15_L 82 0 11 SQ16_D 58 0 32 SQ16_L 58 0 32 SQ17_D 40 0 15 SQ17_L 14 0 15 SQ18_D 29 4 10 SQ18_L 22 0 16 SQ19_D 48 0 4 SQ19_L 48 0 4 SQ20_D 29 0 13 SQ20_L 23 2 9 SQ21_D 58 0 13 SQ21_L 201 0 21 Haplophragmoides Quinqueloculina Trochamminita wilberti seminula salsa SQ01_L 6 6 7 SQ04_D 0 33 2 SQ08_D 0 0 0 SQ08_L 0 0 0 SQ09_D 0 17 0 SQ09_L 0 38 0 SQ10_D 0 11 0 SQ10_L 0 44 0 SQ11_D 0 21 0 SQ11_L 0 0 0 SQ12_D 0 11 0 SQ12_L 0 0 0 SQ13_D 0 0 0 SQ13_L 0 0 0 SQ14_D 0 0 0 SQ14-L 0 0 0 SQ15_D 0 0 0 SQ15_L 0 0 0 SQ16_D 0 0 0 SQ16_L 0 0 0 SQ17_D 0 1 0 SQ17_L 0 0 0 SQ18_D 0 0 0 SQ18_L 0 0 0 SQ19_D 0 0 0 SQ19_L 0 0 0 SQ20_D 0 0 0 SQ20_L 0 0 0 SQ21_D 0 0 0 SQ21_L 0 0 0
Pierre Belart (1), Iara Clemente (2), Debora Raposo (1), Renan Habib (3), Eduardo K. Volino (3) Amanda Villar (1), Maria Virginia Alves Martins (2), Luiz F. Fontana (3), Maria Lucia Lorini (4) Gabriel Panigai (1) Fabrizio Frontalini (5), Marcos S.L. Figueiredo (1), Sergio C. Vasconcelos (6) & Lazaro Laut (3)
(1) Programa de Pos-Graduacao em Biodiversidade Neotropical--PPGBIO/UNIRIO Universidade Federal do Estado do Rio de Janeiro, Rio de Janeiro, Brasil
(2) Departamento de Estratigrafia e Paleontologia, Universidade do Estado do Rio de Janeiro Rio de Janeiro, Brasil
(3) Laboratorio de Micropaleontologia, Universidade Federal do Estado do Rio de Janeiro, Rio de Janeiro, Brasil
(4) Departamento de Ciencias Naturais, Universidade Federal do Estado do Rio de Janeiro Rio de Janeiro, Brasil
(5) Dipartimento di Scienze Pure e Applicate (DiSPeA), Universita degli Studi di Urbino "Carlo Bo" Campus Scientifico "E. Mattei", Localita Crocicchia, Urbino, Italy
(6) Departamento de Geografia e Meio Ambiente, Programa de Pos-Graduacao em Geografia Pontificia Universidade Catolica do Rio de Janeiro, Rio de Janeiro, Brasil
Corresponding author: Pierre Belart (firstname.lastname@example.org)
Corresponding editor: Jose Luis Iriarte
Caption: Figure 1. Localization map of studied stations in the Saquarema Lagoon System.
Caption: Figure 2. Distribution of living and dead foraminiferal density (ind 50 [mL.sup.-1]), species richness, diversity of Shannon and evenness in SLS.
Caption: Figure 3. Species distribution of living and dead density (ind 50 [mL.sup.-1]) of A. parkinsoniana, A. tepida and C. excavatum in SLS.
Caption: Figure 4. Species distribution of living and dead density (ind 50 [mL.sup.-1]) of C. poeyanum, E. gunteri and Q. seminula in SLS.
Caption: Figure 5. DCA analysis relating the living (L) and dead (D) Foraminifera species with the abiotic parameters in SLS. BPC: the total of biopolymers, CHO: carbohydrates, LIP: lipids, PTN: proteins, TS: total sulfur, TOC: total organic carbon, S: salinity, T: temperature.
Caption: Figure 6. Q-mode Cluster Analysis of stations in the SLS based on relative abundance of living (L) and dead (D) foraminifera (Appendix 2). a) Five groups were defined considering 78% of similarity. In bold are the stations where the L- and D-assemblages compose the same group, b) the distribution map of the stations where the L and D-assemblages have at least 78% similarity according to the cluster analysis results.
Table 1. Geographic coordinates of stations, grain size, total organic carbon (TOC; %), total sulphur (TS; %), carbohydrates (CHO; mg C [g.sup.-1]), lipids (LIP; mg C [g.sup.-1]), proteins (PTN; mg C [g.sup.-1]), total biopolymeric carbon (BPC; mg C [g.sup.-1]) are presented. This table also shows salinity (Sal), pH, dissolved oxygen ([O.sub.2]; mg [L.sup.-1]) and temperature (T, [degrees]C) measured at each sampling station. Long Lat (W) (S) SQ01 42[degrees]35'5.63" 22[degrees]55'27.90" SQ02 42[degrees]34'19.55" 22[degrees]55'37.83" SQ03 42[degrees]33'30.27" 22[degrees]55'33.00" SQ04 42[degrees]35'16.65" 22[degrees]54'56.30" SQ05 42[degrees]34'23.95" 22[degrees]54'55.19" SQ06 42[degrees]33'25.69" 22[degrees]54'45.95" SQ07 42[degrees]34'35.83" 22[degrees]53'59.91" SQ08 42[degrees]33'27.18" 22[degrees]53'46.68" SQ09 42[degrees]32'22.21" 22[degrees]55'25.49" SQ10 42[degrees]32'45.95" 22[degrees]54'39.60" SQ11 42[degrees]32'0.49" 22[degrees]54'44.77" SQ12 42[degrees]31'42.99" 22[degrees]55'17.95" SQ13 42[degrees]31'4.91" 22[degrees]55'37.92" SQ14 42[degrees]30'26.15" 22[degrees]54'44.39" SQ15 42[degrees]29'46.12" 22[degrees]54'57.39" SQ16 42[degrees]29'11.66" 22[degrees]54'47.40" SQ17 42[degrees]30'49.99" 22[degrees]55'8.12" SQ18 42[degrees]29'41.91" 22[degrees]55'23.36" SQ19 42[degrees]28'59.72" 22[degrees]55'14.20" SQ20 42[degrees]29'56.69" 22[degrees]55'46.96" SQ21 42[degrees]29'19.20" 22[degrees]55'36.72" SQ22 42[degrees]29'32.31" 22[degrees]56'0.11" O2 T (mg [L.sup.-1]) pH ([degrees]C) Sal SQ01 7.3 8.5 26.3 32.8 SQ02 7.8 8.7 25.8 33.5 SQ03 8.3 8.7 26.6 33.1 SQ04 7.4 8.6 27.7 33.3 SQ05 7.8 8.6 27.7 31.6 SQ06 6.7 8.5 28.3 31.2 SQ07 7.2 8.4 47.9 31.1 SQ08 7.0 8.4 27.6 30.7 SQ09 7.9 8.7 26 33.8 SQ10 5.5 8.2 26.8 33.5 SQ11 5.9 8.2 27.6 31.0 SQ12 6.1 8.5 27.8 31.8 SQ13 6.1 8.6 27.5 32.4 SQ14 6.9 8.4 26.9 34.3 SQ15 7.2 8.5 26.1 34.5 SQ16 .07 8.6 26 34.0 SQ17 7.2 8.5 26 34.0 SQ18 6.4 8.4 25.4 43.3 SQ19 6.5 8.5 26.1 34.1 SQ20 6.4 7.8 24.9 34.5 SQ21 6.8 8.4 26.4 34.0 SQ22 6.7 8.2 25.7 34.3 PTN CHO (mg C [g.sup.-1]) (mg C [g.sup.-1]) SQ01 3.5 11.9 SQ02 2.4 25.9 SQ03 2.7 4.6 SQ04 3.0 13.9 SQ05 2.6 19.8 SQ06 2.7 14.2 SQ07 2.8 23.4 SQ08 3.4 13.3 SQ09 2.7 21.5 SQ10 4.6 10.3 SQ11 2.8 20.1 SQ12 2.6 24.7 SQ13 2.7 19.3 SQ14 2.7 19.8 SQ15 2.3 21.3 SQ16 2.4 20.1 SQ17 2.6 24.0 SQ18 2.1 22.7 SQ19 2.7 21.5 SQ20 2.0 3.1 SQ21 2.2 5.7 SQ22 0.4 1.1 LPI BPC TOC TS Sand (mg C [g.sup.-1]) (mg C [g.sup.-1]) (%) (%) (%) SQ01 2.8 18.2 11.9 3.4 1.5 SQ02 3.0 31.4 10.2 3.7 5.0 SQ03 1.6 8.9 0.5 0.1 99.9 SQ04 3.3 20.2 12.7 4.5 0.7 SQ05 3.3 25.7 10.7 4.2 2.3 SQ06 3.3 20.2 10.1 4.6 0.3 SQ07 3.1 29.3 9.4 4.6 1.9 SQ08 2.9 19.6 11.9 5 10.3 SQ09 3.4 27.6 8.4 3.3 25.7 SQ10 3.6 18.5 21.5 3.4 13.4 SQ11 3.7 26.7 9.3 3.9 13.2 SQ12 3.4 30.8 8.4 3.1 1.1 SQ13 3.1 25.1 6.5 2.9 17.4 SQ14 2.7 25.1 5.2 3.0 4.1 SQ15 2.5 26.1 5.1 2.8 3.2 SQ16 3.0 25.5 4.0 2.8 2.9 SQ17 2.8 29.4 5.3 2.4 13.5 SQ18 2.2 27.0 4.0 2.2 25.3 SQ19 3.5 27.8 4.2 1.7 6.4 SQ20 0.7 5.8 0.3 0 100 SQ21 1.1 9.1 0.2 0 100 SQ22 0.2 1.7 0.1 0.2 100 Silt Clay (%) (%) SQ01 71.6 26.8 SQ02 70.9 24.1 SQ03 0.0 0.1 SQ04 80.2 19.1 SQ05 70.3 27.4 SQ06 60.3 39.4 SQ07 53.2 45.0 SQ08 55.3 34.4 SQ09 57.6 16.7 SQ10 56.9 29.7 SQ11 48.9 37.9 SQ12 66.8 32.1 SQ13 57.6 25.0 SQ14 74.1 21.8 SQ15 75.5 21.3 SQ16 73.8 23.3 SQ17 57.1 29.4 SQ18 42.8 31.9 SQ19 73.6 20.1 SQ20 0 0 SQ21 0 0 SQ22 0 0
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|Title Annotation:||Research Article|
|Author:||Belart, Pierre; Clemente, Iara; Raposo, Debora; Habib, Renan; Volino, Eduardo K.; Villar, Amanda; Ma|
|Publication:||Latin American Journal of Aquatic Research|
|Date:||Nov 1, 2018|
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