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Concentration, stock and transport rate of heavy metals in a tropical red mangrove, Natal, Brazil
Marine Chemistry 99 (2006) 2 – 11 www.elsevier.com/locate/marchem
Concentration, stock and transport rate of heavy metals in a tropical red mangrove, Natal, Brazil C.A. Ramos e Silva*, A.P. da Silva, S.R. de Oliveira Departamento de Oceanografia e Limnologia (Laborato´rio de Biogeoquı´mica Ambiental), Universidade Federal do Rio Grande do Norte, Natal/RN, CEP 59075-970, Brazil Received 8 October 2004; received in revised form 14 September 2005; accepted 14 September 2005 Available online 18 January 2006
Abstract This paper discusses distribution, dynamics and mass budget of heavy metals in a red mangrove forest of the Potengi River estuary, northern Brazil. Tidal hydrology, net primary productivity, decomposing rate of leaf and standing stock of leaf litter in a red mangrove forest were taken into consideration. The belowground roots represented the main mass budget of Fe, Zn and Pb (419.73 mol ha 1, 2.29 mol ha 1 and 0.72 mol ha 1). Differently, Al (683.05 mol ha 1) was mostly present in aerial roots, Cd (1.33 mol ha 1) in the branches and Ni in the trunks (4.43 mol ha 1). Cr showed no significant difference among the structures of Rhizophora mangle (from 0.02 Amol ha 1 to 0.96 mol ha 1). The average litter fall value was 12.3 t ha 1 year 1 whereas the leaves contributed with 9.5 t ha 1 year 1 (78%), the reproductive parts with 1.4 t ha 1 year 1 (11%) and the branches with 1.4 t ha 1 year 1 (11%). The annual average transfer rates of heavy metals from the tree canopy to the sediment through leaf fall were: 0.56, 1.11, 0.01, 0.02 and 0.07 mol ha 1 for Fe, Al, Pb, Zn and Ni respectively. Cu, Cr and Cd fluxes were less than 0.02 mol ha 1. An experiment on yellow leaf decomposition was carried out for different periods: 1, 2, 3, 7, 30, 60 and 90 days. The leaves in the litter bags lost 50% of their dry weight in 30 days. The rate of mass loss was faster in the first 7 days when the leaves lost 21.02% of their initial mass. Concentrations of heavy metals in the decomposing leaves showed a sharp rise from the beginning up to 90 days. However, since the residence time of leaves in the sediments was only 15 days, the leaf litter exported from the mangrove forest is still relatively low in metal concentrations. Considering that 7% of leaf fall (0.7 t ha 1 year 1) is exported to the marginal marine system, the average export of heavy metals through leaf litter is: 0.36, 0.02, 0.004, 0.01, 0.001, 0.005, 0.03 and 0.74 Amol ha 1 year 1 for Fe, Zn, Cr, Cu, Cd, Pb, Ni and Al, respectively. These data support the opinion that mangrove forest is an efficient biogeochemical barrier to the transport of heavy metals to Brazilian coastal areas. D 2005 Elsevier B.V. All rights reserved. Keywords: Red mangrove; Mass budget; Transfer; Potengy estuary; Brazil
1. Introduction The mangrove trees can be considered as a bchemical reactorsQ not only because of their physiological and biochemical processes but also due to their active role in sediment reactions that greatly influence * Corresponding author. E-mail address: [email protected] (C.A. Ramos e Silva). 0304-4203/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.marchem.2005.09.010
the mobility of heavy metals (Defew et al., 2005; Machado et al., 2005; MacFarlane and Burchett, 2000; Silva et al., 1998; Silva, 1996). Examples of such reactions include exudation of oxygen to rhizosphere that reacts with Fe2+ forming Fe3+ (Smolders and Roelofs, 1996). Moreover, organic matter from leaf fall contributes to the depletion of dissolved oxygen in the sediment with a consequent influence on the mobility of heavy metals (Aragon et al., 1999, Nickerson
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and Thibodeau, 1985). Mangrove plants are able to survive under strong physicochemical gradients, including areas exposed to trace metal pollution. (Chiu et al., 1995; MacFarlane and Burchett, 2000). The cycling of organic matter through litter production, decomposition and tidal transport, may eventually export a fraction of the accumulated heavy metals, and therefore convey it to detritus food chains in adjacent coastal waters. Previous studies have suggested that mangroves are long-term sinks for most heavy metals (Harbison, 1986; Silva et al., 1990; Yim and Tam, 1999). However, there is little knowledge about the role of litter production, decomposition and export in the heavy metal cycling in mangrove forests is almost inexistent. In Brazil, for example, we have knowledge only about the study of Silva et al. (1998), carried out in the southern region. This paper addresses the question if Rhizophora mangle trees are an efficient biogeochemical barrier to the export of heavy metals from their inland sources to Brazilian coastal areas and the problem of mangrove sediment to feed the animals. 2. Study site The Potengi estuary, which is located in the state of Rio Grande do Norte, northern Brazil (05844VS and 35811VW, 05851VS and 35821VW) (see Fig. 1), is formed by the waters of the Potengi, Jundiaı´ and Doce rivers. The Potengi River, which drains a catchment of 3180 km2, is 176 km long and discharges approximately 5
3
m3 s 1 in the rainy period (February to August). The Jundiaı´ River has an independent catchment and with its smaller discharge it is more influenced by the tides, whose effects of which have been observed as far as the city of Macaı´ba, 30 km from the mouth of the estuary. The Doce River is the smallest freshwater input to the estuary with a discharge of approximately 2 m3 s 1 during most of the time. Water temperatures vary from 26.5 to 29.0 8C throughout the year. The Potengi estuary extends for about 25 km with a width ranging between 400 and 600 m. The estuary is bordered by three cities with a total population above 1,000,000 inhabitants. The number of cars that cross the Igapo´ Bridge over the estuary per day is approximately 27,000. One of the cities, Natal, discharges more than 60% of its untreated sewage sludge directly into the Potengi river and there are several other point sources of organic effluent along the estuary. Furthermore a number of port and industrial activities are well developed, including leather and textile industries which discharge effluent into the estuary. Silva et al. (2001) and Silva et al. (2003) found trace metal pollution and contamination along the estuary using oyster Crassostrea rhizophorae as a biomonitor. These authors argued that anthropogenic activities, such as dredging, agricultural use of metal-containing fertilizers and pesticides, and the emission of untreated sewage and metal-contaminated effluents from medical use and textile and leather industrial units, are sources of Fe, Mn, Zn, Cu, Ni, Ag, Pb and Cr in the estuary.
Fig. 1. Map of the studied area.
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3. Materials and methods 3.1. The standing stock of heavy metals in R. mangle trees Seven working units, quadrates of 100 m2, were established perpendicularly to the sea at approximately 45 m from the Doce River and 18 m from the forest seaward edge. In each quadrate, all trees were counted, whereas half of them were measured for height and diameter and results extrapolated to 1 ha (Citron and Schaefer-Novelli, 1983). For the estimation of total aboveground biomass, a regression curve was drawn using the total dry weight (trunks, branches, prop roots and leaves) and the diameter of eight cut trees, ranging from 2.1 to 18.7 cm. From the curve, estimates of the weight of all trees in the quadrates could be obtained and then summed up. This was possible since the total aboveground biomass was significantly correlated with tree diameter. The dry biomass of belowground roots was estimated by digging eight 0.25 m2 areas to 25 cm depth where roots were collected, washed in sea water and ovendried (60 8C) in laboratory to constant weight. The results were extrapolated to 1 ha (Silva et al., 1991). Different parts of the R. mangle trees (leaves, branches, trunks, prop roots) were analyzed to determine the heavy metal concentrations. Plant samples were collected from 10 trees representative of the dominant class of tree diameter in the forest. The field samples were packed in plastic bags and taken to the laboratory. They were washed with tap water, ovendried (60 8C for 96 h) and ground for metals analysis. The standing stock of metals in R. mangle trees was calculated by multiplying metal concentrations in each compartment by its biomass in 1 ha. 3.2. Litter fall Litter fall was collected at 30-day intervals, from August 1997 to July 1998, in seventeen 1.0 m2 nylon baskets (1 mm mesh) hung approximately 1.5 m above the ground. The material from each basket was dried at 60 8C up to constant weight and separated into leaves, reproductive parts and thin branches (less than 2 cm in diameter). Only leaves were used to estimate the transfer of metals from the R. mangle trees to the sediment due to their higher relative importance. 3.3. Leaf decomposition A leaf decomposition experiment was carried out from March to May 1998. Senescent R. mangle leaves,
yellow in colour and ready to fall were picked from the trees and allocated in the field. The leaves were split into 24 samples, each one weighing 30 g. Each sample was placed in a separate nylon bag (16 cm 21 cm) with 1.0 mm mesh size, large enough to permit the entry of small invertebrates, but preventing large consumers, such as crabs, which actually cut the leaves. Twenty-one bags were attached to R. mangle roots in contact with surface mud and subject to intertidal conditions. Three bags were retrieved from the site, on each of subsequent days after beginning of the experiment: days 1, 2, 3, 7, 30, 60 and 90. In the laboratory, the sediment was removed from the leaves by gently rubbing the leaves under running tap water and the samples were dried to a constant weight for 96 h at 60 8C. After these procedures, the samples were prepared for heavy metal analysis. Average conversion factors for the subsequent comparison with the dry mass of field results were evaluated according to the following simple regression model: dw ¼ 0:3742fw 0:0019fw2 ; dw ¼ dry weight;
fw ¼ fresh weight:
Percentage of dry weight loss was plotted against time in order to evaluate the half-life (the time required by the leaves to loose one-half of their dry weight) of decomposition of the R. mangle leaves. The rate at which dry weight was lost was calculated using a single exponential model: Wt ¼ W0 dekdt ; where W t is the remaining dry weight at time t, W 0 is the initial leaf dry weight, k is the decay constant and e is the base of natural logarithm (Olson, 1963). This model has been frequently used in mangrove decomposition studies (Citron and Schaefer-Novelli, 1983). Independent duplicates of heavy metals from mix leaves samples (3 bags) were made on 1.0-g samples. The samples were oven-dried (60 8C, 96 h) and ashed (450 8C, 24 h). 3.4. Standing stock of heavy metals in the leaf litter The standing stock of leaf litter was measured during 6 months by collecting each time 15 samples of litter from the surface of the forest floor, in squares of 0.25 m2 (0.5 m 0.5 m), in the vicinity of the litter fall collectors. Surface leaf samples were processed in the same manner as litter fall samples. In the laboratory, the sediment was removed from the leaves by gently rubbing the leaves in running tap water and the samples were dried at 60 8C for 96 h.
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After these procedures, the samples were prepared for heavy metal analysis.
surface of the forest floor and L is the average leaf fall flux in mass vs. time (Olson, 1963).
3.5. Residence time of leaf litter
3.6. Transference of heavy metals from R. mangle trees to the sediment
Zn
0.20
The transference of heavy metals through R. mangle leaf fall to the sediment was calculated by multiplying the mean concentrations in leaf fall, in Amol g 1 µmol.g-1
µmol.g-1
The residence time of leaf litter on the surface of the forest floor was determined using the mathematical model: 1/k = X SS/L, where 1/k is the residence time, X SS is the average standing stock of leaves on the
0.15
0.08
0.05
0.04 0.00 B
T
PR
BGR Structures
Al
60.0
B
µmol.g-1
µmol.g-1
L
45.0
PR
BGR Structures
Pb
0.10 0.08
30.0
0.05
15.0
0.03 0.00
0.0 L
B
T
PR
BGR Structures
Fe
80.0
L
µmol.g-1
µmol.g-1
0.12
0.10
0.00
Cd
0.16
60.0
B
T
PR
BGR Structures
PR
BGR Structures
PR
BGR Structures
Cu
0.06 0.05 0.04 0.03
40.0
0.02
20.0 0.01 0.00
0.0 L
B
T
PR
BGR Structures
L
B
Ni µmol.g-1
µmol.g-1
Cr
T
0.07 0.06 0.05
0.25 0.20
0.04
0.15
0.03
0.10
0.02 0.05
0.01
0.00
0 L
B
T
PR
BGR Structures
L
B
T
Fig. 2. Mean concentrations and ranges (Amol g 1 dry weight) in different structures of R. mangle: leaves (L), branches (B), trunks (T), prop roots (PR), and belowground roots (BGR).
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(Fe = 0.55 F 0.11, Zn = 0.015 F 0.006, Ni = 0.06 F 0.02, Al = 1.11 F 0.67, Cd = 0.0009 F 0.0008, Pb = 0.009 F 0.002, Cu = 0.008 F 0.003 and Cr = 0.006 F 0.005) by the mean leaf fall rate (1000 kg ha 1 month 1).
The highest average concentrations for Pb (0.03 Amol g 1), Zn (0.11 Amol g 1), Fe (23.85 Amol g 1), and Cu (0.04 Amol g 1) were detected in the belowground roots. It is well known that metal-rich deposits on roots of aquatic plants may moderate the uptake of potentially toxic metals (Silva et al., 1990; Smolders and Roelofs, 1996). Oxidation of reduced compounds in pore waters by rhizosphere oxidation can induce a partial precipitation of trace metals (i.e., Fe(OH)3 and MnO2) on the root surfaces and promote a coprecipitation of others metals. The highest average concentration for Cr (0.03 Amol g 1) and Ni (0.12 Amol g 1) are in the trunks, while the leaves presented the lowest concentrations for Ni (0,05 Amol g 1), Cr (0.004 Amol g 1), Fe (0.87 Amol g 1) and Cd (b8.90 10 6 Amol g 1). The highest average concentrations for Cd (0.08 Amol g 1) are in the branches. Yim and Tam (1999) declared that leaf tissues accumulate small amounts of heavy metals, while branch and root tissues accumulated large amounts of heavy metals. A number of researchers have so measured high concentrations of accumulated heavy metals in the tissues of mangrove species with no effect on plant health (MacFarlane et al., 2003; MacFarlane and Burchett, 2002).
3.7. Analysis of heavy metals Biological samples (2 g dry weight) were ashed (450 8C, 12 h). The ashes were digested with concentrated reagent grade HNO3 at 80 8C on a hot plate till dryness and then dissolved in 10 mL of 0.5 M HCl. Trace metals were determined in these extracts through conventional flame atomic absorption spectrophotometry. All samples were run in duplicate, differences among duplicates were always less than 5%, and all digestion procedures were tested with reference material (IEAE336 blichenQ). Differences between certified and measured results were always less than 20%. 3.8. Statistical analysis One-way analysis of variance (ANOVA) followed by Tukey’s multiple comparison test were employed to test any significant difference in metal concentrations among different parts of R. mangle trees at the p b 0.05 level. All statistical analyses were performed using bStatistica version 5.0Q.
4.2. Standing stock of heavy metals in R. mangle trees 4. Results and discussion Table 1 shows that the main reservoir of Fe, Zn and Pb is represented by belowground roots (512.85, 2.29 and 0.724 mol ha 1, respectively), whereas leaves contain the less important stock for Fe (3.76 mol ha 1), for Zn (0.15 mol ha 1), for Pb (0.048 mol ha 1), for Ni (0.17 mol ha 1), for Cu (0.05 mol ha 1) and for Cd (b0.009 mol ha 1). In turn, prop roots store the highest amounts of Al and Cu (683.05 and 0.94 mol ha 1, respectively), whereas branches and trunks present the highest standing stock of Cd (1.33 mol ha 1) and Ni (4.43 mol ha 1), respectively. Finally, Cr did not show
4.1. Heavy metal concentrations The Fig. 2 shows the average concentration of heavy metals in different parts of R. mangle trees. The prop roots have significantly higher concentrations of Al (24.13 Amol g 1) in relation to others biological structures according to one-way ANOVA. On the other hand, no significant difference in Al concentrations was observed among branches, trunks, belowground roots and leaves.
Table 1 Biomass and stock of heavy metals in R. mangle structures in Potengi mangrove forest Structures
Biomass (t ha 1)
Leaves Branches Trunks Prop roots BGRa
4.42 16.45 36.80 28.30 21.50
a
BGR = belowground roots.
Stock (mol ha 1) Fe
Al
Zn
Pb
Ni
Cu
Cr
Cd
3.76 35.28 47.99 181.22 512.85
14.08 68.56 63.00 683.05 5.56
0.15 0.46 1.38 0.46 2.29
0.048 0.290 0.241 0.145 0.724
0.17 1.36 4.43 2.04 1.87
0.05 0.31 0.31 0.94 0.79
0.019 0.192 1.154 0.577 0.385
b0.009 1.334 b0.009 1.068 1.156
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1,5
Litterfall (t ha-1 month-1)
Leaf
Branch
Reproductive Parts
1
0,5
Jul
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Sep
Ago
0
Time 97
98
Fig. 3. Litter fall contents (leaf, branch and reproductive parts) collected during 1 year in Potengi estuary Forest.
any significant difference among structures of R. mangle trees. Perennial tissues accounted for the major pool of Fe, Zn, Pb, Cd, Cu, Cr, Ni, and Al (99.5%; 96.2%, 97.6%, 100.0%, 98.3%, 99.2%, 97.3%, and 98.2%, respectively), where deciduous tissues (leaves) accounted for an insignificant portion of the total metal content, even if they represent nearly 4.0% of the total biomass. This result shows that mangrove forest is an important biogeochemical barrier for heavy metals. Silva et al. (1990) found the same scenario in a red mangrove in Sepetiba Bay, Brazil. 4.3. Litter fall and transport of heavy metals to the sediment Litter fall is an important factor in the cycling of heavy metals in mangrove ecosystem. Through litter fall, metals incorporated into organic matter are transferred to surficial sediments, and eventually released by litter decomposition.
Table 2 Heavy metals month transfer (mol ha 1) from R. mangle leaves to sediment Month
Fe
Al
Pb
Zn
Ni
Cu
Cr
Cd
Aug/97 Sep/97 Oct/97 Apr/98 May/98 Jun/98 Jul/98 Average S.D.
0.54 0.54 0.36 0.36 0.36 0.36 0.36 0.41 0.09
0.74 0.005 0.02 0.03 0.02 b0.019 b0.009 1.11 0.010 0.02 0.05 b0.02 b0.019 b0.009 1.11 0.005 0.02 0.07 0.02 b0.019 b0.009 1.11 0.005 b0.02 0.03 b0.02 b0.019 b0.009 0.74 0.005 0.02 0.05 b0.02 b0.019 b0.009 0.74 0.005 0.02 0.03 b0.02 b0.019 b0.009 0.37 0.005 0.02 0.03 b0.02 b0.019 b0.009 0.85 0.005 0.02 0.05 b0.02 b0.019 b0.009 0.30 b0.005 b0.02 0.02 b0.02 – –
The rate of total litter fall was measured monthly. The highest values were recorded in November 1997 (1.19 t ha 1) and December 1997 (1.28 t ha 1) (dry season) and in June 1998 (1.27 t ha 1) (rainy season). The annual production through photosynthesis was about 12.35 t ha 1 where leaves accounted to 78% (9.5 t ha 1) of the total litter fall (Fig. 3), a value close to those found in the literature (from 4.82 t ha 1 year 1 to 17.7 t ha 1 year 1; Golley et al., 1962; Chale, 1996). The statistical test did not show correlations among litter fall, precipitation and wind. The monthly fluxes (kg ha 1) of heavy metals (Fe, Al, Pb, Zn, Ni, Cu, Cr and Cd) from the trees to the sediment through leaf fall did not have significant differences ( p N 0.05) (Table 2). The average annual inputs of heavy metals to sediments were: 0.56 g ha 1 for Fe, 1.11 mol ha 1 for Al; 0.010 mol ha 1 for Pb, 0.02 mol ha 1 for Zn; 0.07 mol ha 1 for Ni. Values for Cu, Cr and Cd were less than 0.02 mol ha 1. The turnover rates is the ratio of a metal in aboveground biomass of R. mangle trees divided by the transfer of the metal through yearly leaves litter fall. Turnover rates depend on biomass, leaf litter produc-
Table 3 Loss of 50% dry weight in leaves of red mangrove Site
Species
Days
Author
Kenya Thailand USA Panama Brazil Brazil
R. R. R. R. R. R.
14a–35b 40 45 27 77 32
Bosire et al., 2005 Boonruang, 1978 Heald, 1971 D’Croz et al., 1989 Silva et al., 1998 This work
a b
Wet season. Dry season.
mucronata apiculata mangle mangle mangle mangle
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tion and metal contents in the components of the trees. The turnover rates of Fe, Al, Pb, Zn and Ni are 479, 747, 72, 123 and 114 years, respectively. The high turnover rate of heavy metal found in this work is an important indicative that mangrove trees in tropical estuaries act as an important barrier to transport of heavy metals. 4.4. Decomposition and metals release
µmol.g-1
At the beginning of the experiment (first 7 days) a fast loss of R. mangle leaves dry weight (21% of initial
dry weight) was observed. After this period, the loss of dry biomass was slower reaching 50% (half-life) of its initial dry biomass in 32 days and the decomposition rate (k) was 0.02. The first period (7 days) of decomposition was characterized by leaching and fast releasing of soluble compounds. The second period (after 7 days) was characterized by a slower decomposition through biological processes. However, this decomposition rate is high when compared with the results from similar experiments that are listed in Table 3. The reason may be the frequent inundation of the forest (70% of the total annual tidal excursion).
0.10
Pb Cu
0.08 0.06 0.04 0.02 0.00 0
1
2
3
7
15
30
60
90
µmol.g-1
Days
1.20
Ni Zn
0.90
Cr 0.60
0.30
0.00 0
1
2
3
7
15
30
60
90
µmol.g-1
Days
0.10
Pb Cu
0.08 0.06 0.04 0.02 0.00
0
1
2
3
7
15
30
60
90 Days
Fig. 4. Percentage of mass leaf decrease of R. mangle in decomposition experiment.
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Changes in heavy metal concentrations of fallen leaves are due to the effects of leaching, decomposition, accumulative adsorption process, and microorganism growth. Concentrations decreased during the leaching phase (first 7 days) for Cr (55%), Pb (10%), and Cu (50%). After day 30, concentration increased substantially for all metals (Fig. 4). In general, the concentrations of Cr (0.47 Amol g 1), Zn (0.27 Amol g 1), Ni (0.30 Amol g 1), Pb (0.03 Amol g 1), Cu (0.05 Amol g 1), Fe (287 Amol g 1) and Al (259 Amol g 1) after 90 days in the leaf detritus were higher than those in the original falling leaves by 10, 6, 8, 2, 14, 223 and 84 times, respectively. It is well known that in natural water organic particles carry a negative charge so cationic heavy metals may be absorbed by simple electrostact attraction as well as by ion-exchange, simple surface adsorption and coprecipitation with iron hydrous oxides. Therefore, these particles might be influencing heavy metal concentrations in the decomposing leaves.
Litter fall transfer (mol ha-1 yr -1) Fe = 0.555 Ni = 0.068 Al = 1.112 Cu = 0.008 Cd = 0.001 Cr = 0.006 Pb = 0.010 Zn = 0.015
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4.5. Residence times of leaf litter The measured standing stock of leaf litter was 0.42 F 0.28 t ha 1 (n = 90). Therefore, the estimated mean residence time was 15 days, assuming an average annual leaf litter fall rate of 9.5 t ha 1 year 1. It is known that mangrove litter residence time is quite variable depending mostly on the tidal range (Twilley, 1985; Ong et al., 1982), the elevation of the forest relative to inundation (Twilley et al., 1986) and the activity of litter-feeding organisms in particular of seasarmid crabs (Robertson, 1986). Twilley et al. (1986) reported a residence time of 2 to 6 months in a basin forest. This long residence time is due to infrequent flooding of a basin forest, while our forest is a fringe type which is flooded nearly twice every day. In riverine Rhizophorae forests, Ong et al. (1982) found a residence time of leaves of about 30 days. Robertson (1986) showed that crabs can bury over 75% of total litter fall at low tide, speeding the bexportatQ of depos-
Litter export (mol ha-1 yr -1) Fe = 0.358 Ni = 0.034 Al = 0.741 Cu = 0.006 Cd = 0.001 Cr = 0.004 Pb = 0.005 Zn = 0.015
Fig. 5. Dynamics of heavy metals in Potengi estuary forest (PEF).
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ited leaves. In our forest, the activity of seasarmid crabs, evaluated visually, is very high and may contribute to the short residence time of leaves in sediment. 4.6. The exportation of metals associated with leaf litter The export of metals from the mangrove forest to adjacent coastal waters through leaf litter is a function of the amount of litter exported and its metal concentrations, which in turn depend on the residence time of litter on the forest floor and the enrichment of metals during litter decomposition (Silva et al., 1998). The short residence time (15 days) of leaf litters in our forest limits the enrichment of heavy metal in the decomposing leaves. Therefore, the concentrations of metals in leaf litter exported from the forest are equal or slightly higher than the concentrations in recently fallen leaves. Silva et al. (1998) found the same results in a red mangrove located in the Southeast of Brazil. Considering that residence time of leaves in the sediment was 15 days, it can be concluded that leaf litter exported from the mangrove forest has relatively low metal concentrations. Furthermore, assuming that 7% of leaf fall (0.7 t ha 1 year 1) is exported to the marginal marine system (Silva et al., 1998), it is possible to estimate the average exports of heavy metals through leaf litter: 0.36, 0.02, 0.004, 0.01, 0.001, 0.005, 0.03 and 0.07 mol ha 1 year 1 for Fe, Zn, Cr, Cu, Cd, Pb, Ni and Al, respectively. The low values are due to the low values of both export of leaf litters and metal concentrations in decomposing leaves. The metals reached their highest concentrations at day 90 of the experiment (Fig. 4). At this stage, R. mangle leaves became less buoyant and are retained within the mangrove ecosystem, where a relatively fast sedimentation rate cause the burial of decomposed organic matter (Silva et al., 1998). 5. Conclusions Mangrove leaf fall is of the greatest importance in metal cycling in tropical mangrove forests because its organic matter is capable of controlling the mobility of heavy metals. Fig. 5 summarizes the internal cycling of Fe, Ni, Al, Cu, Cd, Cr, Pb and Zn within the mangrove forest. In the R. mangle trees, the main metal mass budget is represented by the perennial tissues (belowground roots, prop roots, trunks and branches) which make mangrove trees a natural barrier for heavy metals. Furthermore, the decomposing leaf litter does not contribute significantly to enhance the metal export
through the tides once the decomposing leaf exported is poor of heavy metal concentrations (residence time is 15 days). On the other hand, it is important to plan a policy to monitor metal contamination of animals that are fed from organic mangrove sediment. Concluding, Brazilian mangrove forests probably are an important and efficient ally of the Government against metal pollution which creates undesired effects in estuaries since the effects are incompatible with the main potential uses of these systems. Acknowledgements The authors wish to acknowledge the International Foundation of Science (IFS-D/2382-1). The first author is grateful by comments of reviewer (DR. Mauro Frignani) which were particularly helpful for improving this manuscript. References Aragon, G.T., Ovalle, A.R.C., Carmouze, J-P., 1999. Porewater and the formation of iron sulfides in a mangrove ecosystem, Sepetiba Bay, Brazil. Mangroves and Salt Marshes 3, 85 – 93. Boonruang, G.P., 1978. The degradation rates of mangrove leaves of Rhizophora apiculata (Bl.) and Avicennia marina (Forsk.) Vierh. at Phuket Island, Thailand. Phuket Marine Biological Centre 26, 1 – 7. Bosire, J.O., Dahdouh-Guebas, F., Kairo, J.G., Kazungu, J., Dehairs, F., Koedam, N., 2005. Litter degradation and CN dynamics in reforested mangrove plantations at Gazi Bay, Kenya. Biological Conservation 126, 287 – 295. Chale, F.M.M., 1996. Litter production in an Avicennia germinans (L.) stearn forest in Guyana, south America. Hidrobiologia 330, 47 – 53. Chiu, C.Y., Hsiu, F.S., Chen, S.S., Chou, C.H., 1995. Reduced toxicity of Cu and Zn to mangrove seedlings (Kandelia candel (L.) Druce) in saline environments. Botanical Bulletin of Academia Sinica 36, 725 – 731. Citron, G., Schaefer-Novelli, Y., 1983. Introduccio´n a la ecologı´a del manglar. UNESCO/ROSTLAC, Montevideo, p. 109. D’Croz, L., DelRosario, J., Holness, R., 1989. Mangrove (Rhizophora mangle L.) leaves in the Bay of Panama. Revista de Biologia Tropical 37, 101 – 104. Defew, L.H., Mair, J.M., Guzman, H.M., 2005. An assessment of metal contamination in mangrove sediments and leaves from Punta Mala Bay, Pacific Panama. Marine Pollution Bulletin 50, 547 – 552. Golley, F.B., Odum, H.T., Wilson, R.F., 1962. The structure and metabolism of a Puerto Rican red mangrove forest in May. Ecology 43, 10 – 19. Harbison, P., 1986. Mangrove muds–a sink and source for trace metals. Marine Pollution Bulletin 17, 273 – 276. Heald, E.J., 1971. The production of organic detritus in a south Florida estuary. Sea Grant Technical Bulletin vol. 6. University of Miami, Coral Gables, Fla., USA. MacFarlane, G.R., Burchett, M.D., 2000. Cellular distribution of copper, lead and zinc in the grey mangrove, Avicennia marina (Forsk.) Vierh. Aquatic Botany 68, 45 – 59.
C.A. Ramos e Silva et al. / Marine Chemistry 99 (2006) 2–11 MacFarlane, G.R., Burchett, M.D., 2002. Toxicity, growth and accumulation relationships of cooper, lead and zinc in the grey mangrove Avicennia marina (Forsk.) Veirh. Marine Environmental Research 54, 65 – 84. MacFarlane, G.R., Pulkownik, A., Burchett, M.D., 2003. Accumulation and distribution of heavy metals in the grey mangrove, Avicennia marina (Fork.) Vierh: biological indication potential. Environmental Pollution 123, 139 – 151. Machado, W., Silva-Filho, E.V., Oliveira, R.R., Lacerda, L.D., 2005. Trace metal retention in mangrove ecosystems in Guanabara Bay, SE Brazil. Marine Pollution Bulletin 44, 1277 – 1280. Nickerson, N.H., Thibodeau, F.R., 1985. Association between pore water sulfide concentrations and the distribution of mangroves. Biogeochemistry 1, 183 – 192. Olson, J.S., 1963. Energy storage and the balance of producers and decomposers in ecological systems. Ecology 42 (2), 322 – 330. Ong, J.E., Gong, W.K., Wong, C.H., 1982. Productivity and nutrient status of litter in a managed mangrove forest in Malaysia. In: Kostermans, A.V., Sastroutomo, S.S. (Eds.), Proc. Symp. Bangor, Indonesia, Biotropica Special Publication vol. 17, pp. 33 – 41. Robertson, A.I., 1986. Leaf-burying crabs: their influence on energy flow and transport from mixed mangrove forests (Rhizophora spp.) in northeastern Australia. Journal of Experimental Marine Biology and Ecology 102, 237 – 248. Silva, C.A.R., 1996. Manguezal: ecossistema egoı´sta ou benevolente? Ciencia Hoje 20 (120), 6 – 11. Silva, C.A.R., Lacerda, L.D., Rezende, C.E., 1990. Heavy metal reservoirs in a red mangrove forest. Biotropica 22, 339 – 345.
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Silva, C.A.R., Lacerda, L.D., Silva, L.F.F., Rezende, C.E., 1991. Forest structure and biomass distribution in a red mangrove stand in Sepetiba Bay, Rio de Janeiro. Revista Brasileira de Botanica 14, 21 – 25. Silva, C.A.R., Lacerda, L.D., Ovalle, A.R., Rezende, C.E., 1998. The dynamics of heavy metals through litter fall and decomposition in a red mangrove forest. Mangroves and Salt Marshes 2, 149 – 157. Silva, C.A.R., Rainbow, P.S., Smith, B.D., 2001. Biomonitoring of trace metal contamination in the Potengi estuary, Natal (Brazil), using the oyster Crassostrea rhizophgohae, a local food source. Water Research 35 (17), 4072 – 4078. Silva, C.A.R., Raimbow, P.S., Smith, B.D., 2003. Biomonitoring of trace metal contamination in the mangrove-lined Brazilian coastal system using the oyster Crassostrea rhizophgohae: comparative study of regions affected by oil, salt pond and shrimp farming activities. Hydrobiologia 501, 199 – 206. Smolders, A.J.P., Roelofs, J.G.M., 1996. The roles of internal iron hydroxide precipitation, sulphide toxicity and oxidizing ability in the survival of Stratiotes aloides roots at different iron concentrations in sediment pore water. New Phytologist 133, 253 – 260. Twilley, R.R., 1985. The exchange of organic carbon in basin mangrove forests in a southwest Florida estuary. Estuarine, Coastal and Shelf Science 20, 543 – 557. Twilley, R.R., Lugo, A.E., Patterson-Zucca, C., 1986. Litter production and turnover in basin mangrove forests in southwest Florida. Ecology 67, 670 – 683. Yim, M.W., Tam, N.F.Y., 1999. Effects of wastewater-borne heavy metals on mangrove plants and soil microbial activities. Marine Pollution Bulletin 39, 179 – 186.
Concentration, stock and transport rate of heavy metals in a tropical red mangrove, Natal, Brazil C.A. Ramos e Silva*, A.P. da Silva, S.R. de Oliveira Departamento de Oceanografia e Limnologia (Laborato´rio de Biogeoquı´mica Ambiental), Universidade Federal do Rio Grande do Norte, Natal/RN, CEP 59075-970, Brazil Received 8 October 2004; received in revised form 14 September 2005; accepted 14 September 2005 Available online 18 January 2006
Abstract This paper discusses distribution, dynamics and mass budget of heavy metals in a red mangrove forest of the Potengi River estuary, northern Brazil. Tidal hydrology, net primary productivity, decomposing rate of leaf and standing stock of leaf litter in a red mangrove forest were taken into consideration. The belowground roots represented the main mass budget of Fe, Zn and Pb (419.73 mol ha 1, 2.29 mol ha 1 and 0.72 mol ha 1). Differently, Al (683.05 mol ha 1) was mostly present in aerial roots, Cd (1.33 mol ha 1) in the branches and Ni in the trunks (4.43 mol ha 1). Cr showed no significant difference among the structures of Rhizophora mangle (from 0.02 Amol ha 1 to 0.96 mol ha 1). The average litter fall value was 12.3 t ha 1 year 1 whereas the leaves contributed with 9.5 t ha 1 year 1 (78%), the reproductive parts with 1.4 t ha 1 year 1 (11%) and the branches with 1.4 t ha 1 year 1 (11%). The annual average transfer rates of heavy metals from the tree canopy to the sediment through leaf fall were: 0.56, 1.11, 0.01, 0.02 and 0.07 mol ha 1 for Fe, Al, Pb, Zn and Ni respectively. Cu, Cr and Cd fluxes were less than 0.02 mol ha 1. An experiment on yellow leaf decomposition was carried out for different periods: 1, 2, 3, 7, 30, 60 and 90 days. The leaves in the litter bags lost 50% of their dry weight in 30 days. The rate of mass loss was faster in the first 7 days when the leaves lost 21.02% of their initial mass. Concentrations of heavy metals in the decomposing leaves showed a sharp rise from the beginning up to 90 days. However, since the residence time of leaves in the sediments was only 15 days, the leaf litter exported from the mangrove forest is still relatively low in metal concentrations. Considering that 7% of leaf fall (0.7 t ha 1 year 1) is exported to the marginal marine system, the average export of heavy metals through leaf litter is: 0.36, 0.02, 0.004, 0.01, 0.001, 0.005, 0.03 and 0.74 Amol ha 1 year 1 for Fe, Zn, Cr, Cu, Cd, Pb, Ni and Al, respectively. These data support the opinion that mangrove forest is an efficient biogeochemical barrier to the transport of heavy metals to Brazilian coastal areas. D 2005 Elsevier B.V. All rights reserved. Keywords: Red mangrove; Mass budget; Transfer; Potengy estuary; Brazil
1. Introduction The mangrove trees can be considered as a bchemical reactorsQ not only because of their physiological and biochemical processes but also due to their active role in sediment reactions that greatly influence * Corresponding author. E-mail address: [email protected] (C.A. Ramos e Silva). 0304-4203/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.marchem.2005.09.010
the mobility of heavy metals (Defew et al., 2005; Machado et al., 2005; MacFarlane and Burchett, 2000; Silva et al., 1998; Silva, 1996). Examples of such reactions include exudation of oxygen to rhizosphere that reacts with Fe2+ forming Fe3+ (Smolders and Roelofs, 1996). Moreover, organic matter from leaf fall contributes to the depletion of dissolved oxygen in the sediment with a consequent influence on the mobility of heavy metals (Aragon et al., 1999, Nickerson
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and Thibodeau, 1985). Mangrove plants are able to survive under strong physicochemical gradients, including areas exposed to trace metal pollution. (Chiu et al., 1995; MacFarlane and Burchett, 2000). The cycling of organic matter through litter production, decomposition and tidal transport, may eventually export a fraction of the accumulated heavy metals, and therefore convey it to detritus food chains in adjacent coastal waters. Previous studies have suggested that mangroves are long-term sinks for most heavy metals (Harbison, 1986; Silva et al., 1990; Yim and Tam, 1999). However, there is little knowledge about the role of litter production, decomposition and export in the heavy metal cycling in mangrove forests is almost inexistent. In Brazil, for example, we have knowledge only about the study of Silva et al. (1998), carried out in the southern region. This paper addresses the question if Rhizophora mangle trees are an efficient biogeochemical barrier to the export of heavy metals from their inland sources to Brazilian coastal areas and the problem of mangrove sediment to feed the animals. 2. Study site The Potengi estuary, which is located in the state of Rio Grande do Norte, northern Brazil (05844VS and 35811VW, 05851VS and 35821VW) (see Fig. 1), is formed by the waters of the Potengi, Jundiaı´ and Doce rivers. The Potengi River, which drains a catchment of 3180 km2, is 176 km long and discharges approximately 5
3
m3 s 1 in the rainy period (February to August). The Jundiaı´ River has an independent catchment and with its smaller discharge it is more influenced by the tides, whose effects of which have been observed as far as the city of Macaı´ba, 30 km from the mouth of the estuary. The Doce River is the smallest freshwater input to the estuary with a discharge of approximately 2 m3 s 1 during most of the time. Water temperatures vary from 26.5 to 29.0 8C throughout the year. The Potengi estuary extends for about 25 km with a width ranging between 400 and 600 m. The estuary is bordered by three cities with a total population above 1,000,000 inhabitants. The number of cars that cross the Igapo´ Bridge over the estuary per day is approximately 27,000. One of the cities, Natal, discharges more than 60% of its untreated sewage sludge directly into the Potengi river and there are several other point sources of organic effluent along the estuary. Furthermore a number of port and industrial activities are well developed, including leather and textile industries which discharge effluent into the estuary. Silva et al. (2001) and Silva et al. (2003) found trace metal pollution and contamination along the estuary using oyster Crassostrea rhizophorae as a biomonitor. These authors argued that anthropogenic activities, such as dredging, agricultural use of metal-containing fertilizers and pesticides, and the emission of untreated sewage and metal-contaminated effluents from medical use and textile and leather industrial units, are sources of Fe, Mn, Zn, Cu, Ni, Ag, Pb and Cr in the estuary.
Fig. 1. Map of the studied area.
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3. Materials and methods 3.1. The standing stock of heavy metals in R. mangle trees Seven working units, quadrates of 100 m2, were established perpendicularly to the sea at approximately 45 m from the Doce River and 18 m from the forest seaward edge. In each quadrate, all trees were counted, whereas half of them were measured for height and diameter and results extrapolated to 1 ha (Citron and Schaefer-Novelli, 1983). For the estimation of total aboveground biomass, a regression curve was drawn using the total dry weight (trunks, branches, prop roots and leaves) and the diameter of eight cut trees, ranging from 2.1 to 18.7 cm. From the curve, estimates of the weight of all trees in the quadrates could be obtained and then summed up. This was possible since the total aboveground biomass was significantly correlated with tree diameter. The dry biomass of belowground roots was estimated by digging eight 0.25 m2 areas to 25 cm depth where roots were collected, washed in sea water and ovendried (60 8C) in laboratory to constant weight. The results were extrapolated to 1 ha (Silva et al., 1991). Different parts of the R. mangle trees (leaves, branches, trunks, prop roots) were analyzed to determine the heavy metal concentrations. Plant samples were collected from 10 trees representative of the dominant class of tree diameter in the forest. The field samples were packed in plastic bags and taken to the laboratory. They were washed with tap water, ovendried (60 8C for 96 h) and ground for metals analysis. The standing stock of metals in R. mangle trees was calculated by multiplying metal concentrations in each compartment by its biomass in 1 ha. 3.2. Litter fall Litter fall was collected at 30-day intervals, from August 1997 to July 1998, in seventeen 1.0 m2 nylon baskets (1 mm mesh) hung approximately 1.5 m above the ground. The material from each basket was dried at 60 8C up to constant weight and separated into leaves, reproductive parts and thin branches (less than 2 cm in diameter). Only leaves were used to estimate the transfer of metals from the R. mangle trees to the sediment due to their higher relative importance. 3.3. Leaf decomposition A leaf decomposition experiment was carried out from March to May 1998. Senescent R. mangle leaves,
yellow in colour and ready to fall were picked from the trees and allocated in the field. The leaves were split into 24 samples, each one weighing 30 g. Each sample was placed in a separate nylon bag (16 cm 21 cm) with 1.0 mm mesh size, large enough to permit the entry of small invertebrates, but preventing large consumers, such as crabs, which actually cut the leaves. Twenty-one bags were attached to R. mangle roots in contact with surface mud and subject to intertidal conditions. Three bags were retrieved from the site, on each of subsequent days after beginning of the experiment: days 1, 2, 3, 7, 30, 60 and 90. In the laboratory, the sediment was removed from the leaves by gently rubbing the leaves under running tap water and the samples were dried to a constant weight for 96 h at 60 8C. After these procedures, the samples were prepared for heavy metal analysis. Average conversion factors for the subsequent comparison with the dry mass of field results were evaluated according to the following simple regression model: dw ¼ 0:3742fw 0:0019fw2 ; dw ¼ dry weight;
fw ¼ fresh weight:
Percentage of dry weight loss was plotted against time in order to evaluate the half-life (the time required by the leaves to loose one-half of their dry weight) of decomposition of the R. mangle leaves. The rate at which dry weight was lost was calculated using a single exponential model: Wt ¼ W0 dekdt ; where W t is the remaining dry weight at time t, W 0 is the initial leaf dry weight, k is the decay constant and e is the base of natural logarithm (Olson, 1963). This model has been frequently used in mangrove decomposition studies (Citron and Schaefer-Novelli, 1983). Independent duplicates of heavy metals from mix leaves samples (3 bags) were made on 1.0-g samples. The samples were oven-dried (60 8C, 96 h) and ashed (450 8C, 24 h). 3.4. Standing stock of heavy metals in the leaf litter The standing stock of leaf litter was measured during 6 months by collecting each time 15 samples of litter from the surface of the forest floor, in squares of 0.25 m2 (0.5 m 0.5 m), in the vicinity of the litter fall collectors. Surface leaf samples were processed in the same manner as litter fall samples. In the laboratory, the sediment was removed from the leaves by gently rubbing the leaves in running tap water and the samples were dried at 60 8C for 96 h.
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5
After these procedures, the samples were prepared for heavy metal analysis.
surface of the forest floor and L is the average leaf fall flux in mass vs. time (Olson, 1963).
3.5. Residence time of leaf litter
3.6. Transference of heavy metals from R. mangle trees to the sediment
Zn
0.20
The transference of heavy metals through R. mangle leaf fall to the sediment was calculated by multiplying the mean concentrations in leaf fall, in Amol g 1 µmol.g-1
µmol.g-1
The residence time of leaf litter on the surface of the forest floor was determined using the mathematical model: 1/k = X SS/L, where 1/k is the residence time, X SS is the average standing stock of leaves on the
0.15
0.08
0.05
0.04 0.00 B
T
PR
BGR Structures
Al
60.0
B
µmol.g-1
µmol.g-1
L
45.0
PR
BGR Structures
Pb
0.10 0.08
30.0
0.05
15.0
0.03 0.00
0.0 L
B
T
PR
BGR Structures
Fe
80.0
L
µmol.g-1
µmol.g-1
0.12
0.10
0.00
Cd
0.16
60.0
B
T
PR
BGR Structures
PR
BGR Structures
PR
BGR Structures
Cu
0.06 0.05 0.04 0.03
40.0
0.02
20.0 0.01 0.00
0.0 L
B
T
PR
BGR Structures
L
B
Ni µmol.g-1
µmol.g-1
Cr
T
0.07 0.06 0.05
0.25 0.20
0.04
0.15
0.03
0.10
0.02 0.05
0.01
0.00
0 L
B
T
PR
BGR Structures
L
B
T
Fig. 2. Mean concentrations and ranges (Amol g 1 dry weight) in different structures of R. mangle: leaves (L), branches (B), trunks (T), prop roots (PR), and belowground roots (BGR).
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(Fe = 0.55 F 0.11, Zn = 0.015 F 0.006, Ni = 0.06 F 0.02, Al = 1.11 F 0.67, Cd = 0.0009 F 0.0008, Pb = 0.009 F 0.002, Cu = 0.008 F 0.003 and Cr = 0.006 F 0.005) by the mean leaf fall rate (1000 kg ha 1 month 1).
The highest average concentrations for Pb (0.03 Amol g 1), Zn (0.11 Amol g 1), Fe (23.85 Amol g 1), and Cu (0.04 Amol g 1) were detected in the belowground roots. It is well known that metal-rich deposits on roots of aquatic plants may moderate the uptake of potentially toxic metals (Silva et al., 1990; Smolders and Roelofs, 1996). Oxidation of reduced compounds in pore waters by rhizosphere oxidation can induce a partial precipitation of trace metals (i.e., Fe(OH)3 and MnO2) on the root surfaces and promote a coprecipitation of others metals. The highest average concentration for Cr (0.03 Amol g 1) and Ni (0.12 Amol g 1) are in the trunks, while the leaves presented the lowest concentrations for Ni (0,05 Amol g 1), Cr (0.004 Amol g 1), Fe (0.87 Amol g 1) and Cd (b8.90 10 6 Amol g 1). The highest average concentrations for Cd (0.08 Amol g 1) are in the branches. Yim and Tam (1999) declared that leaf tissues accumulate small amounts of heavy metals, while branch and root tissues accumulated large amounts of heavy metals. A number of researchers have so measured high concentrations of accumulated heavy metals in the tissues of mangrove species with no effect on plant health (MacFarlane et al., 2003; MacFarlane and Burchett, 2002).
3.7. Analysis of heavy metals Biological samples (2 g dry weight) were ashed (450 8C, 12 h). The ashes were digested with concentrated reagent grade HNO3 at 80 8C on a hot plate till dryness and then dissolved in 10 mL of 0.5 M HCl. Trace metals were determined in these extracts through conventional flame atomic absorption spectrophotometry. All samples were run in duplicate, differences among duplicates were always less than 5%, and all digestion procedures were tested with reference material (IEAE336 blichenQ). Differences between certified and measured results were always less than 20%. 3.8. Statistical analysis One-way analysis of variance (ANOVA) followed by Tukey’s multiple comparison test were employed to test any significant difference in metal concentrations among different parts of R. mangle trees at the p b 0.05 level. All statistical analyses were performed using bStatistica version 5.0Q.
4.2. Standing stock of heavy metals in R. mangle trees 4. Results and discussion Table 1 shows that the main reservoir of Fe, Zn and Pb is represented by belowground roots (512.85, 2.29 and 0.724 mol ha 1, respectively), whereas leaves contain the less important stock for Fe (3.76 mol ha 1), for Zn (0.15 mol ha 1), for Pb (0.048 mol ha 1), for Ni (0.17 mol ha 1), for Cu (0.05 mol ha 1) and for Cd (b0.009 mol ha 1). In turn, prop roots store the highest amounts of Al and Cu (683.05 and 0.94 mol ha 1, respectively), whereas branches and trunks present the highest standing stock of Cd (1.33 mol ha 1) and Ni (4.43 mol ha 1), respectively. Finally, Cr did not show
4.1. Heavy metal concentrations The Fig. 2 shows the average concentration of heavy metals in different parts of R. mangle trees. The prop roots have significantly higher concentrations of Al (24.13 Amol g 1) in relation to others biological structures according to one-way ANOVA. On the other hand, no significant difference in Al concentrations was observed among branches, trunks, belowground roots and leaves.
Table 1 Biomass and stock of heavy metals in R. mangle structures in Potengi mangrove forest Structures
Biomass (t ha 1)
Leaves Branches Trunks Prop roots BGRa
4.42 16.45 36.80 28.30 21.50
a
BGR = belowground roots.
Stock (mol ha 1) Fe
Al
Zn
Pb
Ni
Cu
Cr
Cd
3.76 35.28 47.99 181.22 512.85
14.08 68.56 63.00 683.05 5.56
0.15 0.46 1.38 0.46 2.29
0.048 0.290 0.241 0.145 0.724
0.17 1.36 4.43 2.04 1.87
0.05 0.31 0.31 0.94 0.79
0.019 0.192 1.154 0.577 0.385
b0.009 1.334 b0.009 1.068 1.156
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1,5
Litterfall (t ha-1 month-1)
Leaf
Branch
Reproductive Parts
1
0,5
Jul
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Sep
Ago
0
Time 97
98
Fig. 3. Litter fall contents (leaf, branch and reproductive parts) collected during 1 year in Potengi estuary Forest.
any significant difference among structures of R. mangle trees. Perennial tissues accounted for the major pool of Fe, Zn, Pb, Cd, Cu, Cr, Ni, and Al (99.5%; 96.2%, 97.6%, 100.0%, 98.3%, 99.2%, 97.3%, and 98.2%, respectively), where deciduous tissues (leaves) accounted for an insignificant portion of the total metal content, even if they represent nearly 4.0% of the total biomass. This result shows that mangrove forest is an important biogeochemical barrier for heavy metals. Silva et al. (1990) found the same scenario in a red mangrove in Sepetiba Bay, Brazil. 4.3. Litter fall and transport of heavy metals to the sediment Litter fall is an important factor in the cycling of heavy metals in mangrove ecosystem. Through litter fall, metals incorporated into organic matter are transferred to surficial sediments, and eventually released by litter decomposition.
Table 2 Heavy metals month transfer (mol ha 1) from R. mangle leaves to sediment Month
Fe
Al
Pb
Zn
Ni
Cu
Cr
Cd
Aug/97 Sep/97 Oct/97 Apr/98 May/98 Jun/98 Jul/98 Average S.D.
0.54 0.54 0.36 0.36 0.36 0.36 0.36 0.41 0.09
0.74 0.005 0.02 0.03 0.02 b0.019 b0.009 1.11 0.010 0.02 0.05 b0.02 b0.019 b0.009 1.11 0.005 0.02 0.07 0.02 b0.019 b0.009 1.11 0.005 b0.02 0.03 b0.02 b0.019 b0.009 0.74 0.005 0.02 0.05 b0.02 b0.019 b0.009 0.74 0.005 0.02 0.03 b0.02 b0.019 b0.009 0.37 0.005 0.02 0.03 b0.02 b0.019 b0.009 0.85 0.005 0.02 0.05 b0.02 b0.019 b0.009 0.30 b0.005 b0.02 0.02 b0.02 – –
The rate of total litter fall was measured monthly. The highest values were recorded in November 1997 (1.19 t ha 1) and December 1997 (1.28 t ha 1) (dry season) and in June 1998 (1.27 t ha 1) (rainy season). The annual production through photosynthesis was about 12.35 t ha 1 where leaves accounted to 78% (9.5 t ha 1) of the total litter fall (Fig. 3), a value close to those found in the literature (from 4.82 t ha 1 year 1 to 17.7 t ha 1 year 1; Golley et al., 1962; Chale, 1996). The statistical test did not show correlations among litter fall, precipitation and wind. The monthly fluxes (kg ha 1) of heavy metals (Fe, Al, Pb, Zn, Ni, Cu, Cr and Cd) from the trees to the sediment through leaf fall did not have significant differences ( p N 0.05) (Table 2). The average annual inputs of heavy metals to sediments were: 0.56 g ha 1 for Fe, 1.11 mol ha 1 for Al; 0.010 mol ha 1 for Pb, 0.02 mol ha 1 for Zn; 0.07 mol ha 1 for Ni. Values for Cu, Cr and Cd were less than 0.02 mol ha 1. The turnover rates is the ratio of a metal in aboveground biomass of R. mangle trees divided by the transfer of the metal through yearly leaves litter fall. Turnover rates depend on biomass, leaf litter produc-
Table 3 Loss of 50% dry weight in leaves of red mangrove Site
Species
Days
Author
Kenya Thailand USA Panama Brazil Brazil
R. R. R. R. R. R.
14a–35b 40 45 27 77 32
Bosire et al., 2005 Boonruang, 1978 Heald, 1971 D’Croz et al., 1989 Silva et al., 1998 This work
a b
Wet season. Dry season.
mucronata apiculata mangle mangle mangle mangle
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tion and metal contents in the components of the trees. The turnover rates of Fe, Al, Pb, Zn and Ni are 479, 747, 72, 123 and 114 years, respectively. The high turnover rate of heavy metal found in this work is an important indicative that mangrove trees in tropical estuaries act as an important barrier to transport of heavy metals. 4.4. Decomposition and metals release
µmol.g-1
At the beginning of the experiment (first 7 days) a fast loss of R. mangle leaves dry weight (21% of initial
dry weight) was observed. After this period, the loss of dry biomass was slower reaching 50% (half-life) of its initial dry biomass in 32 days and the decomposition rate (k) was 0.02. The first period (7 days) of decomposition was characterized by leaching and fast releasing of soluble compounds. The second period (after 7 days) was characterized by a slower decomposition through biological processes. However, this decomposition rate is high when compared with the results from similar experiments that are listed in Table 3. The reason may be the frequent inundation of the forest (70% of the total annual tidal excursion).
0.10
Pb Cu
0.08 0.06 0.04 0.02 0.00 0
1
2
3
7
15
30
60
90
µmol.g-1
Days
1.20
Ni Zn
0.90
Cr 0.60
0.30
0.00 0
1
2
3
7
15
30
60
90
µmol.g-1
Days
0.10
Pb Cu
0.08 0.06 0.04 0.02 0.00
0
1
2
3
7
15
30
60
90 Days
Fig. 4. Percentage of mass leaf decrease of R. mangle in decomposition experiment.
C.A. Ramos e Silva et al. / Marine Chemistry 99 (2006) 2–11
Changes in heavy metal concentrations of fallen leaves are due to the effects of leaching, decomposition, accumulative adsorption process, and microorganism growth. Concentrations decreased during the leaching phase (first 7 days) for Cr (55%), Pb (10%), and Cu (50%). After day 30, concentration increased substantially for all metals (Fig. 4). In general, the concentrations of Cr (0.47 Amol g 1), Zn (0.27 Amol g 1), Ni (0.30 Amol g 1), Pb (0.03 Amol g 1), Cu (0.05 Amol g 1), Fe (287 Amol g 1) and Al (259 Amol g 1) after 90 days in the leaf detritus were higher than those in the original falling leaves by 10, 6, 8, 2, 14, 223 and 84 times, respectively. It is well known that in natural water organic particles carry a negative charge so cationic heavy metals may be absorbed by simple electrostact attraction as well as by ion-exchange, simple surface adsorption and coprecipitation with iron hydrous oxides. Therefore, these particles might be influencing heavy metal concentrations in the decomposing leaves.
Litter fall transfer (mol ha-1 yr -1) Fe = 0.555 Ni = 0.068 Al = 1.112 Cu = 0.008 Cd = 0.001 Cr = 0.006 Pb = 0.010 Zn = 0.015
9
4.5. Residence times of leaf litter The measured standing stock of leaf litter was 0.42 F 0.28 t ha 1 (n = 90). Therefore, the estimated mean residence time was 15 days, assuming an average annual leaf litter fall rate of 9.5 t ha 1 year 1. It is known that mangrove litter residence time is quite variable depending mostly on the tidal range (Twilley, 1985; Ong et al., 1982), the elevation of the forest relative to inundation (Twilley et al., 1986) and the activity of litter-feeding organisms in particular of seasarmid crabs (Robertson, 1986). Twilley et al. (1986) reported a residence time of 2 to 6 months in a basin forest. This long residence time is due to infrequent flooding of a basin forest, while our forest is a fringe type which is flooded nearly twice every day. In riverine Rhizophorae forests, Ong et al. (1982) found a residence time of leaves of about 30 days. Robertson (1986) showed that crabs can bury over 75% of total litter fall at low tide, speeding the bexportatQ of depos-
Litter export (mol ha-1 yr -1) Fe = 0.358 Ni = 0.034 Al = 0.741 Cu = 0.006 Cd = 0.001 Cr = 0.004 Pb = 0.005 Zn = 0.015
Fig. 5. Dynamics of heavy metals in Potengi estuary forest (PEF).
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C.A. Ramos e Silva et al. / Marine Chemistry 99 (2006) 2–11
ited leaves. In our forest, the activity of seasarmid crabs, evaluated visually, is very high and may contribute to the short residence time of leaves in sediment. 4.6. The exportation of metals associated with leaf litter The export of metals from the mangrove forest to adjacent coastal waters through leaf litter is a function of the amount of litter exported and its metal concentrations, which in turn depend on the residence time of litter on the forest floor and the enrichment of metals during litter decomposition (Silva et al., 1998). The short residence time (15 days) of leaf litters in our forest limits the enrichment of heavy metal in the decomposing leaves. Therefore, the concentrations of metals in leaf litter exported from the forest are equal or slightly higher than the concentrations in recently fallen leaves. Silva et al. (1998) found the same results in a red mangrove located in the Southeast of Brazil. Considering that residence time of leaves in the sediment was 15 days, it can be concluded that leaf litter exported from the mangrove forest has relatively low metal concentrations. Furthermore, assuming that 7% of leaf fall (0.7 t ha 1 year 1) is exported to the marginal marine system (Silva et al., 1998), it is possible to estimate the average exports of heavy metals through leaf litter: 0.36, 0.02, 0.004, 0.01, 0.001, 0.005, 0.03 and 0.07 mol ha 1 year 1 for Fe, Zn, Cr, Cu, Cd, Pb, Ni and Al, respectively. The low values are due to the low values of both export of leaf litters and metal concentrations in decomposing leaves. The metals reached their highest concentrations at day 90 of the experiment (Fig. 4). At this stage, R. mangle leaves became less buoyant and are retained within the mangrove ecosystem, where a relatively fast sedimentation rate cause the burial of decomposed organic matter (Silva et al., 1998). 5. Conclusions Mangrove leaf fall is of the greatest importance in metal cycling in tropical mangrove forests because its organic matter is capable of controlling the mobility of heavy metals. Fig. 5 summarizes the internal cycling of Fe, Ni, Al, Cu, Cd, Cr, Pb and Zn within the mangrove forest. In the R. mangle trees, the main metal mass budget is represented by the perennial tissues (belowground roots, prop roots, trunks and branches) which make mangrove trees a natural barrier for heavy metals. Furthermore, the decomposing leaf litter does not contribute significantly to enhance the metal export
through the tides once the decomposing leaf exported is poor of heavy metal concentrations (residence time is 15 days). On the other hand, it is important to plan a policy to monitor metal contamination of animals that are fed from organic mangrove sediment. Concluding, Brazilian mangrove forests probably are an important and efficient ally of the Government against metal pollution which creates undesired effects in estuaries since the effects are incompatible with the main potential uses of these systems. Acknowledgements The authors wish to acknowledge the International Foundation of Science (IFS-D/2382-1). The first author is grateful by comments of reviewer (DR. Mauro Frignani) which were particularly helpful for improving this manuscript. References Aragon, G.T., Ovalle, A.R.C., Carmouze, J-P., 1999. Porewater and the formation of iron sulfides in a mangrove ecosystem, Sepetiba Bay, Brazil. Mangroves and Salt Marshes 3, 85 – 93. Boonruang, G.P., 1978. The degradation rates of mangrove leaves of Rhizophora apiculata (Bl.) and Avicennia marina (Forsk.) Vierh. at Phuket Island, Thailand. Phuket Marine Biological Centre 26, 1 – 7. Bosire, J.O., Dahdouh-Guebas, F., Kairo, J.G., Kazungu, J., Dehairs, F., Koedam, N., 2005. Litter degradation and CN dynamics in reforested mangrove plantations at Gazi Bay, Kenya. Biological Conservation 126, 287 – 295. Chale, F.M.M., 1996. Litter production in an Avicennia germinans (L.) stearn forest in Guyana, south America. Hidrobiologia 330, 47 – 53. Chiu, C.Y., Hsiu, F.S., Chen, S.S., Chou, C.H., 1995. Reduced toxicity of Cu and Zn to mangrove seedlings (Kandelia candel (L.) Druce) in saline environments. Botanical Bulletin of Academia Sinica 36, 725 – 731. Citron, G., Schaefer-Novelli, Y., 1983. Introduccio´n a la ecologı´a del manglar. UNESCO/ROSTLAC, Montevideo, p. 109. D’Croz, L., DelRosario, J., Holness, R., 1989. Mangrove (Rhizophora mangle L.) leaves in the Bay of Panama. Revista de Biologia Tropical 37, 101 – 104. Defew, L.H., Mair, J.M., Guzman, H.M., 2005. An assessment of metal contamination in mangrove sediments and leaves from Punta Mala Bay, Pacific Panama. Marine Pollution Bulletin 50, 547 – 552. Golley, F.B., Odum, H.T., Wilson, R.F., 1962. The structure and metabolism of a Puerto Rican red mangrove forest in May. Ecology 43, 10 – 19. Harbison, P., 1986. Mangrove muds–a sink and source for trace metals. Marine Pollution Bulletin 17, 273 – 276. Heald, E.J., 1971. The production of organic detritus in a south Florida estuary. Sea Grant Technical Bulletin vol. 6. University of Miami, Coral Gables, Fla., USA. MacFarlane, G.R., Burchett, M.D., 2000. Cellular distribution of copper, lead and zinc in the grey mangrove, Avicennia marina (Forsk.) Vierh. Aquatic Botany 68, 45 – 59.
C.A. Ramos e Silva et al. / Marine Chemistry 99 (2006) 2–11 MacFarlane, G.R., Burchett, M.D., 2002. Toxicity, growth and accumulation relationships of cooper, lead and zinc in the grey mangrove Avicennia marina (Forsk.) Veirh. Marine Environmental Research 54, 65 – 84. MacFarlane, G.R., Pulkownik, A., Burchett, M.D., 2003. Accumulation and distribution of heavy metals in the grey mangrove, Avicennia marina (Fork.) Vierh: biological indication potential. Environmental Pollution 123, 139 – 151. Machado, W., Silva-Filho, E.V., Oliveira, R.R., Lacerda, L.D., 2005. Trace metal retention in mangrove ecosystems in Guanabara Bay, SE Brazil. Marine Pollution Bulletin 44, 1277 – 1280. Nickerson, N.H., Thibodeau, F.R., 1985. Association between pore water sulfide concentrations and the distribution of mangroves. Biogeochemistry 1, 183 – 192. Olson, J.S., 1963. Energy storage and the balance of producers and decomposers in ecological systems. Ecology 42 (2), 322 – 330. Ong, J.E., Gong, W.K., Wong, C.H., 1982. Productivity and nutrient status of litter in a managed mangrove forest in Malaysia. In: Kostermans, A.V., Sastroutomo, S.S. (Eds.), Proc. Symp. Bangor, Indonesia, Biotropica Special Publication vol. 17, pp. 33 – 41. Robertson, A.I., 1986. Leaf-burying crabs: their influence on energy flow and transport from mixed mangrove forests (Rhizophora spp.) in northeastern Australia. Journal of Experimental Marine Biology and Ecology 102, 237 – 248. Silva, C.A.R., 1996. Manguezal: ecossistema egoı´sta ou benevolente? Ciencia Hoje 20 (120), 6 – 11. Silva, C.A.R., Lacerda, L.D., Rezende, C.E., 1990. Heavy metal reservoirs in a red mangrove forest. Biotropica 22, 339 – 345.
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