AN ASSESSMENT OF THE PHOSPHORUS RETENTION CAPACITY OF WETLANDS IN THE PAINTER CREEK WATERSHED, MINNESOTA, USA G. L. BRULAND1,2,∗ and C. J. RICHARDSON1 1
Duke University Wetland Center, Nicholas School of the Environment and Earth Sciences, Box 90333, Durham, North Carolina, 27708-0328 U.S.A.; 2 University of Hawaii at Manoa, Department of Natural Resources and Environmental Management, 1910, East-West Rd., Honolulu, HI 96822 (∗ author for correspondence, e-mail:
[email protected]; Tel: (808) 956-8901, Fax: (808) 956-6539)
(Received 17 April 2005; accepted 9 November 2005)
Abstract. Lake Minnetonka, located in southeastern Minnesota, U.S.A., is currently experiencing increased eutrophication due to excessive phosphorus (P) loading in runoff from agriculture and urban areas. This phenomenon has been exacerbated by the isolation of wetlands in the surrounding watershed from the surface water drainage network. In order to determine if rerouting surface water through these wetlands would be a feasible method for reducing P inputs, we assessed the P retention capacity of wetlands in a subwatershed of Lake Minnetonka, the Painter Creek Watershed (PCW). The objectives of our study were to determine which of 15 different wetland sites in the PCW had the highest P sorption capacity, identify which soil properties best explained the variability in P sorption, and utilize P fractionation to determine the dominant form of soil P. Our results indicated that despite similar vegetation and hydrogeomorphic settings, wetlands in the PCW had considerably different P sorption capacities. Depth-averaged P sorption index (PSI) values showed considerable variability, ranging from 14.6 to 184. The Katrina Marsh, Painter Marsh, South Highway 26, and West Jennings Bay sites had the highest depth-averaged PSIs. The soil properties that best predicted PSI were soil organic matter, exchangeable calcium, and oxalate extractable iron. Phosphorus fractionation data revealed organic P to be the dominant form of soil P, indicating that organic matter accumulation is another P storage mechanism in these wetlands. Keywords: Lake Minnetonka, Minnesota, phosphorus fractionation, phosphorous sorption, water quality, watershed, wetland
1. Introduction Phosphorus (P) is considered the most common limiting nutrient in freshwater ecosystems (Schindler, 1977), and increased P loading from non-point source (NPS) runoff can lead to degraded water quality, toxic algal blooms, anoxia, and loss of aquatic biodiversity (Carpenter et al., 1998). As a result of their location in the landscape, wetlands interact with both upstream and upslope sources of NPS runoff and have the ability to markedly reduce NPS inputs of P to surface waters (Brinson, 1993; Walbridge, 1993; Lockaby and Walbridge, 1998). Furthermore, wetland soils have been shown to have higher P sorption capacities than soils of Water, Air, and Soil Pollution (2006) 171: 169–184 DOI: 10.1007/s11270-005-9032-7
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adjacent uplands or streambanks (Axt and Walbridge, 1999; Darke and Walbridge, 2000). Thus, wetlands may function as sinks for P at the landscape scale and if so, play a central role in maintaining regional water quality (Darke and Walbridge, 2000). As development trends in the Minneapolis-St. Paul region of Minnesota suggest increasing losses of natural wetlands and disconnection of wetlands from the surrounding landscape, an understanding of their P storage mechanisms is increasingly critical. A better understanding of the controls on P storage can help to identify which wetlands in a watershed have the highest P storage capacities and could be purposely used to enhance P removal and storage (Lyons et al., 1998). Long-term P storage in wetlands is believed to be controlled by three main processes: (1) deposition of sediment bound P; (2) sorption of dissolved phosphate; or (3) the storage of organic P by peat accretion (Qualls and Richardson, 1995; Richardson, 1999). While significant amounts of P can be stored by sedimentation (Johnston, 1991), these sediments may be re-suspended in future hydrologic events. Consequently, sorption and peat accretion are believed to represent the most important long-term P retention pathways (Richardson, 1999). In alkaline wetland soils, P sorption has been shown to be significantly correlated with calcium and magnesium content, and to a lesser degree with aluminum, iron and soil organic matter (SOM) content (Richardson, 1999). Thus, the objectives of this study were to: (1) determine which of 15 wetland sites in the Painter Creek Watershed (PCW) had the highest P sorption capacity; (2) identify which soil properties best explained the variability in P sorption; and (3) utilize P fractionation to determine the dominant form of soil P in these wetlands. As Lake Minnetonka is a major recreational resource for the Minneapolis-St. Paul region (Getsinger et al., 2000), there is currently a great deal of concern about the increasing frequency of eutrophication episodes that occur therein. However, despite these concerns, no study to date has examined the condition of wetlands in the Lake Minnetonka watershed, or quantified their ability to retain P. Furthermore, Lake Minnetonka is a useful study site, as it is typical of many upper Midwestern hard-water lakes having high biological productivities and underlain by sediment rich in precipitated carbonates (Murchie, 1985). Thus, the approach we use in this study may have utility as a screening processes to identify which wetlands in a watershed have the highest P retention potential not only in other parts of the upper Midwest but also beyond this region. The protection of water quality in freshwater ecosystems, such as Lake Minnetonka, is increasingly vital as it has been argued that freshwater is the most valuable and sought-after resource on earth (Wilson and Carpenter, 1999). 2. Materials and Methods 2.1. STUDY
AREA
The PCW is located to the northwest of the Minneapolis-St. Paul metropolitan area of Minnesota, U.S.A. (Figure 1). Painter Creek itself drains into the northwest
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section of Lake Minnetonka. Lake Minnetonka has a total area of 5801 ha, a mean depth of 6.9 m, and a total volume of 400,000,000 m3 (Smith et al., 1991). Upon entering the lake, water drains eastward into Minnehaha Creek, which eventually flows into the Mississippi River. The geology of the region is characterized by coalesced kettleholes in the rolling St. Croix moraine (Wright, 1972). According to the Hennepin County Soil Survey (Lueth, 1974), the soils of the marshes in the PCW include both mineral soils such as the Hamel series (Typic Argiaquolls) and unclassified organic soils (Terric Medihemists).
Figure 1. Map of the wetland study sites in the Painter Creek Watershed, Minnesota, U.S.A. Section (a.) shows the location of Lake Minnetonka in relation to the state of Minnesota, section (b.) shows the Lake Minnetonka area, and section (c.) shows the Painter Creek Watershed.
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Paleoecological data indicated that land cover of this region consisted of an Acer-Tilia-Quercus-Ulmus forest from about 1650 until 1864 (Grimm, 1983). From 1864 to 1877, agricultural activity decreased forest cover from 75 to 25% (Cooley, 1899). From 1868 to the 1890s, Lake Minnetonka also became a popular resort area. However, in the 1890s, large estates replaced hotels and cottages and the area became a wealthy suburb (Stein, 1971). By the 1930s the entire 175 km shoreline of the lake had been developed. After World War II, the population of the area increased and retail and shopping centers were developed. Water quality of Lake Minnetonka decreased as a result of discharges of phosphate-rich sewage and NPS runoff (Murchie, 1985). During the 1970s, sewage discharges from local communities were diverted from the lake. However, in this same period, the community of Maple Plain continued to discharge sewage into the lake through Painter Creek (Murchie, 1985). Currently, Lake Minnetonka is faced with numerous ecological challenges such as shoreline development, increased nutrient loading, and infestation by the invasive aquatic plant species, Myriophyllum spicatum (Eurasian watermilfoil) (Getsinger et al., 2000). 2.2. S AMPLE
COLLECTION
For this study, 15 soil cores were collected from 10 freshwater herbaceous marshes in the PCW: four cores were taken from the largest wetland, Painter Marsh; two soil cores were taken from the 2nd largest wetland, Katrina Marsh; and nine additional cores were collected from nine smaller wetlands (Table I). Vegetation in these marshes was dominated by Typha spp. (cattail). Although multiple cores were taken from some of the sites and not from the others, we considered each of the cores an independent sample as each represented an independent area through which surface water in ditches and streams could be rerouted to increase P retention in the watershed. A single soil core was collected at each site after clearing snow and ice from the soil surface. A piston-type corer was used to drive a metal sampling tube with an inner diameter of 5 cm to a depth of 30 cm. The cores were collected during the period from 20 February 2003 through 7 March 2003 and were maintained in a frozen state. On 10 March 2003, samples were extruded from the sampling tubes and stored in sealed plastic bags. The samples were then shipped in a cooler with ice to the Duke University Wetland Center Laboratory. 2.3. LABORATORY
ANALYSES OF SOIL PROPERTIES
Upon arrival at the laboratory, the cores were split into three 10 cm sections (0–10, 10–20, 20–30 cm) which were then homogenized by hand. A subsample from each section was oven dried at 105 ◦ C for 24 hours. This dried soil was then used to determine the percent soil organic matter (SOM) by loss on ignition (Campbell et al., 2002) and total P (PT ) content by HNO3 –HClO4 digestion followed by
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TABLE I Characteristics and sampling depths from marshes sampled within the Painter Creek Watershed Site name
Site #
Soil order
Site size (ha)
Collected 0–10,10–20, and 20–30 cm depths
North Highway 12 Katrina Lake East Katrina Lake West Katrina Marsh North Katrina Marsh South Carlson South Potato Farm North North Highway 6 Painter Marsh North Painter Marsh West Painter Marsh Middle Painter Marsh South East Highway 110 South Highway 26 West Jennings Bay
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Terric Medihemist Typic Argiaaquoll Typic Argiaaquoll Terric Medihemist Terric Medihemist Terric Medihemist Terric Medihemist Terric Medihemist Terric Medihemist Terric Medihemist Terric Medihemist Terric Medihemist Terric Medihemist Terric Medihemist Terric Medihemist
15.9 9.5 5.4 25.7 25.7 19.3 11.8 18.1 72.7 72.7 72.7 72.7 22.9 17.1 4.9
0–10, 10–20, 20–32.5 yes 0–10, 10–20, 20–27.5 yes yes yes 0–10, 10–17.5, 17.5–25 yes 0–10, 10–20, 20–40 yes yes 0–17.5a , 17.5–25 0–25b yes 0–10, 10–17.5, 17.5–25
a
Due to limited sample volume this core was split into two rather than three increments. Due to limited sample volume and difficulties extruding the core from the sample tube, this core was not split into increments. b
automated ascorbic acid reduction on a Lachat autoanalyzer (O’Halloran, 1993). Additional subsamples were weighed into crucibles of equal volume and oven dried at 105 ◦ C for 24 hours to determine the disturbed bulk density (Tan, 1996). These disturbed bulk density values will be referred to as bulk density (BD) values for the rest of the paper. The rest of the analyses were done on field moist soils. Soil pH was determined with a 2:1 water to soil ratio (Hendershot et al., 1993). Exchangeable calcium (Caex ) was extracted with 1 N ammonium acetate at pH 7.0 (Jackson, 1958). Amorphous aluminum and iron were extracted with acid ammonium oxalate adjusted to pH 3.0 (Richardson, 1985). Exchangeable Ca and amorphous Al and Fe were analyzed with an atomic absorption Spectrophotometer (PerkinElmer, Boston, MA, U.S.A.). The P sorption index (PSI) was used to quantify the P sorption capacity of the Painter Creek soils (Richardson, 1985). Previous studies have established that the PSI: (1) serves as a reliable gauge of a wetland soil’s P sorption potential; (2) is less time-consuming to measure than multiple-point P sorption isotherms; and (3) facilitates comparison with related soil properties (Richardson, 1985; Axt and Walbridge, 1999; Bridgham et al., 2001). The PSI was determined by shaking 2 g of dry weight equivalent of soil with a 25 mL solution of 130 mg PO4 -P. L−1 for
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24 h. Soils were sterilized with 2 drops of toluene to prevent microbial uptake of P (Richardson and Vaithiyanathan, 1995). After shaking, samples were centrifuged for 20 min and filtered with Whatman 42 filter paper. Samples were analyzed for PO4 -P by Ion Chromatography (Dionex, Sunnyvale, CA). The difference in concentration of PO4 -P between the initial (130) and final concentration represents the amount of P sorbed. The index was then calculated as X. (log C)−1 where X = amount of P sorbed (mg P. 100 g soil−1 ) and C = the final inorganic P concentration in solution (mg PO4 -P. L−1 ). Finally, soils were extracted with a modified P fractionation procedure based on that of Hedley et al. (1982) and Tiessen and Moir (1993). Field moist samples were sequentially extracted with: (a) 0.5 M NaHCO3 ; (b) 0.1 M NaOH; and (c) 1 M HCl. The NaHCO3 extraction was assumed to correspond with bioavailable P, the NaOH extraction to correspond with Al and Fe-bound P, and the HCl extraction to correspond with Ca-bound P. Mineral bound P was assumed to be the sum of the Al and Fe-bound P and the Ca-bound P. After pH neutralization with hydrochloric acid or sodium hydroxide, the sequential fractions were analyzed for molybdate reactive phosphorus (Murphy and Riley, 1962). Organic or residual P was determined by summing the NaHCO3 , NaOH, and HCl fractions and subtracting this amount from the PT concentration. 2.4. STATISTICAL
ANALYSIS
Mean and standard deviation values were calculated for each of the soil properties at the three depth intervals. The mean of the three depth intervals was also calculated for all soil properties measured at each site. These values will be referred to as the depth-averaged soil property values. A Pearson correlation analysis and multiple step-wise regression (MSR) were also employed to determine the relationships among soil properties and the PSI for the cores in each depth interval. Multiple step-wise regression is a statistical tool used to predict the response of a dependent variable from a group of potential predictor variables. For the MSR, PSI was used as the dependent variable and pH, SOM, Caex , Feox , and Alox were used as the independent variables.
3. Results 3.1. PSI
VALUES AND SOIL CHEMISTRY
The mean PSI value for the soil in the upper 10 cm was 101.2 (Table II). For most sites, if the PSI was high at 0–10 cm, it was also high at both the 10–20 and the 20–30 cm and vice versa. While PSI values tended to decrease with depth, there were four sites for which the opposite was true (Potato Farm North [site 7], Painter Marsh Middle [11], West Jennings Bay [13], and South Highway 26 [14]). The
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TABLE II Mean values for the phosphorus sorption index (PSI), bulk density (BD), pH, soil organic matter (SOM), exchangeable calcium (Caex ), oxalate extractable iron (Feox ) and aluminum (Alox ), and total phosphorus (PT ) at the three depth increments across all sites (standard deviations in parenthesis) Depth Interval (cm) 0–10a 10–20b 20–30c
PSI X/logC 101.2 (60.2) 97.3 (66.0) 87.6 (46.8)
BD (g/cm3 )
pH
SOM (%)
Caex (mg/g)
Feox (mg/g)
Alox (mg/g)
PT (μg/g)
0.34 (0.26) 0.36 (0.27) 0.35 (0.21)
7.05 (0.45) 7.08 (0.30) 7.11 (0.27)
42.6 (21.2) 42.1 (20.6) 40.1 (22.1)
7.59 (1.79) 7.53 (2.72) 7.37 (2.82)
3.95 (1.87) 4.17 (2.24) 3.59 (1.71)
0.70 (0.32) 1.03 (0.63) 0.87 (0.27)
1280 (372) 1201 (253) 1076 (308)
n = 15 for this depth increment. n = 13 for this depth increment. c n = 14 for this depth increment. a
b
depth-averaged PSI values for each site displayed considerable variability with a high of 184.4 at Painter Marsh South (site 12), and a low of 14.5 at East Highway 110 (site 13) (Table III). In order to group the sites in terms of their P sorption capacities we classified the five sites with the highest depth-averaged (0–30 cm) PSI values as having a high P sorption capacity, the sites with the next five highest depth-averaged PSI values as having an intermediate P sorption capacity, and the cores with the five lowest depth-averaged PSI values as having low P sorption capacities. According to this grouping, Katrina Marsh South (site 5), Painter Marsh West (10), Painter Marsh South (12), South Highway 26 (14), and West Jennings Bay (15) all had high depth-averaged PSI values. Katrina Marsh North (site 4), Carlson South (6), Potato Farm North (7), Painter Marsh North (9), and Painter Marsh Middle (10) had intermediate depth-averaged PSI values. North Highway 12 (site 1), Katrina Lake East (2), Katrina Lake West (3), North Highway 6 (8), and East Highway 110 (13) all had low depth-averaged PSI values. In terms of position within the watershed, with the exception of East Highway 110, sites in the upper northeast part of the watershed had lower PSI values than sites in the lower southwestern part of the watershed. In terms of marsh size (See Table I), all sites from Painter Marsh and Katrina Marsh, the two largest marshes, had either intermediate or high depth-averaged PSI values while the smaller marshes tended to have intermediate or low PSI values. However, the smallest marsh, West Jennings Bay (site 15), was grouped with the Painter and Katrina marsh sites in the high PSI class. The mean BD in the upper ten cm was 0.34 g/cm3 (Table II). This was comparable to mean BD values at the 10–20 and the 20–30 cm depths. The mean soil pH in the upper ten cm was 7.1 (Table II). There was a slight increase in mean soil pH with depth, although the values remained fairly consistent throughout the profile. The
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TABLE III Depth-averaged values (standard deviation below in parenthesis) over the upper 0–30 cm from the 15 marshes sampled within the Painter Creek Watershed Site name North Hwy 12 Katrina Lake East Katrina Lake West Katrina Marsh North Katrina Marsh South Carlson South Potato Farm North NW Hwy 6 Painter Marsh North Painter Marsh West Painter Marsh Middle Painter Marsh South East Hwy 110 South Hwy 26 West Jennings Bay
PSI X/logC
BD (g/cm3 )
pH
SOM (%)
Caex (mg/g)
Feox (mg/g)
Alox (mg/g)
PT (μg/g)
14.6 (2.3) 22.6 (7.2) 44.9 (17.2) 96.8 (38.1) 143.8 (33.6) 73.5 (12.1) 92.2 (26.5) 66.6 (10.4) 104.5 (7.8) 150.0 (20.1) 114.0 (25.8) 184.4 (39.7) 14.5 (NA)a 154.4 (97.1) 130.4 (28.7)
0.58 (0.15) 0.53 (0.21) 0.50 (0.22) 0.11 (0.01) 0.18 (0.02) 0.43 (0.30) 0.29 (0.09) 0.22 (0.05) 0.35 (0.16) 0.40 (0.19) 0.47 (0.21) 0.17 (0.15) 1.21 (NA) 0.21 (0.07) 0.16 (0.04)
6.75 (0.31) 7.14 (0.34) 7.17 (0.16) 6.87 (0.11) 6.94 (0.08) 7.29 (0.05) 7.15 (0.15) 6.92 (0.02) 7.37 (0.30) 7.68 (0.09) 7.31 (0.12) 6.97 (0.13) 7.80 (NA) 6.76 (0.03) 6.53 (0.19)
10.0 (1.29) 19.0 (4.20) 28.9 (10.10) 75.6 (2.50) 67.0 (1.98) 28.7 (5.35) 37.3 (11.34) 53.0 (2.89) 28.2 (6.83) 45.0 (0.33) 31.8 (2.65) 66.8 (0.31) 4.7 (NA) 54.0 (19.62) 58.3 (9.45)
3.85 (0.21) 7.01 (0.25) 10.57 (3.33) 6.04 (0.38) 9.23 (0.47) 5.94 (0.88) 6.84 (0.88) 6.37 (0.67) 5.52 (1.05) 8.86 (0.49) 6.86 (0.91) 10.76 (1.08) 5.59 (NA) 9.65 (4.38) 9.19 (1.44)
2.66 (0.11) 2.33 (0.35) 2.08 (0.66) 0.94 (0.17) 5.43 (0.83) 2.43 (0.83) 3.29 (0.73) 3.86 (1.35) 6.02 (0.31) 4.74 (0.35) 6.88 (1.81) 6.19 (0.43) 2.79 (NA) 4.58 (2.73) 4.31 (0.38)
0.76 (0.02) 0.68 (0.43) 0.92 (0.12) 0.51 (0.10) 1.13 (0.15) 0.72 (0.28) 0.66 (0.10) 0.88 (0.27) 0.78 (0.07) 0.90 (0.13) 0.64 (0.03) 0.41 (0.21) 0.31 (NA) 1.63 (1.15) 1.37 (0.23)
809 (144) 979 (198) 1184 (248) 974 (76.9) 1194 (128) 809 (88.9) 1111 (353) 1716 (44.9) 1159 (111) 1582 (198) 1259 (167) 1398 (120) 499 (NA) 1250 (246) 1503 (148)
a NA = not applicable as limited sample volume did not allow for the 0–25 cm core to be sectioned into depth intervals.
mean SOM content in the upper ten cm was 42.6% and this value was comparable to the means for the lower two depths. The mean Caex concentration in the upper 10 cm was 7.59 mg/g, and mean values decreased slightly with depth. Mean values for Feox (3.95 mg/g) and Alox (0.70 mg/g) in the upper 0–10 cm were lower than mean
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values of Caex . Additionally, mean values of Feox and Alox were each highest in the 10–20 cm increment. Mean TP was highest in the 0–10 cm (1280 μg/g) increment and exhibited a slight decrease with depth. 3.2. FACTORS
CONTROLLING
P
RETENTION
The Pearson correlation analysis revealed that BD and SOM had significant negative correlations at all three depth intervals (Table IV). Bulk density also had significant negative correlations with PSI in the upper two depth intervals. SOM, TABLE IV Pearson correlation matrices for soil properties from the 0–10 cm, 10–20 cm, and 20–30 cm increments 0–10 cma BD pH SOM Caex Feox Alox PSI 10–20 cmb BD pH SOM Caex Feox Alox PSI 20–30 cmc BD pH SOM Caex Feox Alox PSI
BD
pH
SOM
Caex
Feox
Alox
PSI
ns
−0.76 ns
−0.55 ns 0.60
ns ns ns 0.55
ns ns ns ns ns
−0.62 ns 0.79 0.77 ns ns
BD
pH ns
SOM −0.80 ns
Caex ns ns 0.55
Feox ns ns ns ns
Alox ns −0.60 ns 0.80 ns
PSI −0.54 ns 0.62 0.73 0.76 0.71
BD
pH 0.58
SOM −0.52 ns
Caex ns ns ns
Feox ns ns ns ns
Alox ns ns ns ns ns
PSI ns ns 0.64 ns 0.71 ns
Correlations listed in the table were determined to be significant at the 95% confidence level. (ns = not significant) a n = 15. b n = 13. c n = 14.
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on the other hand, had significant positive correlations with PSI at all depths (Table IV). At the 0–10 and 10–20 cm depths, Caex was significantly correlated to SOM and to the PSI. At the lower two depths, Feox was significantly correlated to PSI, while at the middle depth, Alox was significantly correlated to the PSI. For the 0–10 cm depth increment, multiple step-wise regression (MSR) identified a two-term model based on SOM and Feox that explained 81% of the variation in the PSI [PSI = 2.2(SOM) + 13.6(Feox ) – 45.2]. For the 10–20 cm increment, MSR identified a similar model based on Caex and Feox that explained 82% of the variation in the PSI [PSI = 12.8(Caex ) + 16.9(Feox ) – 69.8]. Again, at the 20–30 cm depths, the MSR identified SOM and Feox as the best predictors of the PSI in a twoterm model that explained 74% of the variation in the PSI [PSI = 1.0(SOM) + 16.2(Feox ) – 12.7]. 3.3. P
FRACTIONATION
In the upper 10 cm, organic P comprised greater than 60% of the total soil P for each of the sites (Figure 2). For six of the sites, organic P comprised greater than 80% of the total P. Calcium-bound P made up less than 5% of the total P at the 0–10 cm depth at all sites. Aluminum and iron-bound P was slightly more variable than Ca-P and comprised 3–20% of the total P. Bioavailable P was also relatively variable, comprising from 1–15% of the total soil P. The Katrina Marsh (sites 4 and 5), Painter Marsh (9–12), and South Highway 26 (14) sites had the highest mineral bound P of all the cores in the upper 0–10 cm. A similar pattern emerged in the 10–20 and 20–30 cm depths with organic P as the dominant P fraction. For example, organic P accounted for greater than 70% of the total soil P for all but one site at the 10–20 cm depth. The exception to this trend was South Highway 26 (site 14), for which organic P only accounted for 60% of the total soil P. The Al and Fe-bound P at this site comprised over 20% of the total P. Likewise, at depths of 20–30 cm below the surface, in all but two sites, organic P comprised greater than 80% of the total P. At the deepest depth increment, Painter Marsh South (site 12) had the highest mineral-bound P, although it should be pointed out that due to limited sample volume, the Painter Marsh South soil in this increment was actually from 17.5–25 cm and not 20–30 cm.
4. Discussion 4.1. PSI
VALUES AND SOIL CHEMISTRY
The decrease in mean PSI with depth across all marshes reported in this study was similar to results documented in a study of riparian wetlands in Virginia (Axt and Walbridge, 1999). In the Virginia study, the higher P sorption capacities of the surface cores (0–15 cm) were attributed to the higher SOM, Al, and
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Figure 2. The composition of the soil P in the Painter Creek wetland soils. The bars are arranged so that the more labile forms are above more refractory forms. The site numbers correspond to those listed in Table I.
Fe contents in the upper soil profile (Axt and Walbridge, 1999). Our PSI values were also slightly higher in the downstream sections of the PCW than the upstream sections. This suggested that marshes in the upper reaches of the watershed have experienced greater P loading and are becoming saturated with P. Our results indicated that wetlands in this region of Minnesota with similar vegetative communities and similar hydrogeomorphic settings have very different P sorption capacities.
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Previous studies of P sorption in wetlands have shown that organic soils with acid pHs have some of the lowest PSI values (Richardson, 1985). These types of sites do not appear to be effective at P sorption due to the lack of mineral soil components that are able to bind with P. In contrast, organic soils with alkaline pHs, such as those of the Painter Creek marshes, have relatively high PSI values, indicating that they may be effective P sinks at the landscape scale. The presence of calcium in these alkaline organic soil marshes, unlike those of the acid organic soil marshes, make this soil environment more conducive to P sorption. While the mean BD values for each of the three depth intervals were nearly identical, there were some differences in the depth-averaged BD values for the individual sites. The two sites with mineral soils (Katrina Lake East and West) had relatively high depth-averaged BD values and the sites with organic soils had relatively lower BDs. However, two sites with organic soils, North Highway 12 and the East Highway 110, also had high BDs. This suggested that soils in the North Highway 12 and the East Highway 110 sites may have experienced compaction or oxidation of surface organic layers. As most of the pH values ranged between 7.0–8.0, the soils sampled in this study were neutral to alkaline. Under such conditions, adsorption and precipitation reactions would be controlled by calcium and magnesium. The slight decrease in Caex values with depth may have caused the decrease in PSI with depth. Our SOM, Feox , and Alox values were similar to those reported in another study of riverine wetlands in northeastern Minnesota (Bridgham et al., 2001). Our mean PT values in the upper 0–20 cm were three times higher than PT values reported for an acid forested floodplain soil in Georgia (350 μg/g) (Wright et al., 2001), nearly double the mean values of two acid soil riverine wetlands in Minnesota (690 and 450 μg/g) (Bridgham et al., 2001), and yet less than values reported for northern Everglades Histosols that have been exposed to anthropogenic P loading and hydrologic alteration (1360 μg/g) (Richardson and Vaithiyanathan, 1995). 4.2. FACTORS
CONTROLLING
P
RETENTION
We determined the soil properties with the strongest correlations to PSI in the PCW to be SOM and Caex . It has been shown that negatively-charged organic matter is able to bind positively-charged cations such as Ca and Mg that then can bind with phosphate to create an organo-metallic P complex (Brady and Weil, 1999). Thus we recommend that future research of P sorption dynamics in the Painter Creek wetlands should focus on factors that control the concentration and distribution of soil calcium including parent material, weathering, and the addition of lime. Multiple step-wise regression indicated that a two term regression model that used Feox and either SOM or Caex could successfully predict PSI values at all three depth intervals. Importantly, when sorption of P is controlled by calcium, the Ca-bound P will not be released under anaerobic conditions, as Ca-P, unlike Fe-P, is not affected by changes in soil redox potential.
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4.3. P
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FRACTIONATION
As the soils of the marshes in the PCW were largely organic, it was not surprising that greater than 60% of the P in these soils was organic P. Our results were similar to those of a previous study of P fractionation in the Florida Everglades, another freshwater marsh system with alkaline soils (Qualls and Richardson, 1995). Thus its appears that soil P pools in organic, alkaline wetland soils are considerably different from soil P pools in other upland mineral soil ecosystems such as grasslands and shrublands where P pools tend to be dominated by Al and Fe-bound P or Ca-bound P (Cross and Schlesinger, 2001). The dominance of organic P fractions at all three depths suggested that organic matter accumulation was another P storage mechanism in the Painter Creek marshes. The stability of this accumulated organic P is critical to the future water quality of the PCW. Changes in land-use and artificial drainage may result in the mineralization of these organic P pools and the release of even greater amounts of P into Painter Creek and eventually into Lake Minnetonka. While organic matter accumulation is an important P storage mechanism for the Painter Creek marsh soils, these soils are also capable of directly sorbing P as they contained mineral material with considerable Al, Fe, and Ca. These mineral soil components can sorb appreciable amounts of P from surface and shallow groundwater. As expected, the marshes with the highest mineral-bound P pools were also the marshes with the highest PSI values. 4.4. MANAGEMENT
RECOMMENDATIONS
Our results suggested that it would be possible to improve the quality of water flowing into Lake Minnetonka by using key wetlands in the PCW as nutrient removal treatment wetlands. Water from ditches and incised streams could be routed through the Katrina, Painter, South Highway 26, and West Jennings Bay marshes, as these are the wetlands in which the highest P sorption is most likely to occur. While routing surface water through these marshes has the potential to improve water quality during the initial period following hydrologic modifications, these marshes may not continue to serve as P sinks on the landscape indefinitely. In addition, other marshes with similar characteristics to those sites identified in this study should be considered for inclusion in a network of P retention wetlands to improve water quality of Lake Minnetonka. This approach should provide a low-cost method to reduce P inputs from the watershed into Lake Minnetonka and hopefully restore a more natural hydrologic regime to the drained wetlands. It should be pointed out that the best long-term solution to reducing P inputs to Lake Minnetonka would be to reduce P usage and sources throughout the watershed through a combination of best management practices, precision agriculture, and improvements to the septic and sewage treatment systems. The approach taken in this study generated a wealth of information about the P retention capacity of marshes in the PCW. Applying this approach to other watersheds,
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one could expect to determine the following: (1) at which the depths in the upper soil profile P sorption was highest; (2) at which wetlands within the watershed was P sorption highest and if a spatial pattern existed in their distribution; (3) what soil properties controlled P sorption; and (4) in what form the soil P was being stored. This would be valuable information that politicians, regulators, managers, and community members could use to implement watershed-based wetland restoration, conservation, or nutrient management plans. The information generated from this screening process could also be incorporated in geographic information system (GIS) databases from which further relationships among watershed characteristics, wetlands, and nutrient retention could be investigated.
5. Conclusions Freshwater marsh sites in the PCW with similar vegetation and hydrology had substantially different mean P sorption capacities. We recommend that water from ditches and incised streams be routed through the Katrina, Painter, South Highway 26, and West Jennings Bay marshes, as these are the areas in which the highest P sorption is most likely to occur. We determined that at all sites, the soil properties that best explained the variability in PSI were SOM, Caex , and Feox . While sorption of phosphates by Ca is expected to occur in these Painter Creek wetlands, the P fractionation results indicated that the majority of P stored in these marshes is stored as organic P. This suggested that organic matter accumulation is another P storage mechanism in these wetlands. The results of this research provide valuable information that could be used to implement watershed-based wetland restoration, conservation, or nutrient management plans.
Acknowledgments We thank the Minnehaha Creek Watershed District for providing funding for this project and G. Oberts of Emmons and Olivier Resources, Inc. for providing useful background information and data. W. Willis and P. Heine of the Duke University Wetland Center conducted the laboratory analysis. Comments on earlier versions of this manuscript by H. Bruland, K. Bruland, and A. Sutton-Grier are also gratefully acknowledged. References Axt, J. R. and Walbridge, M. R.: 1999, ‘Phosphate removal capacity of palustrine forested wetlands and adjacent uplands in Virginia’, Soil Sci. Soc. Am. J. 63, 1019–1031. Brady, N. C. and Weil, R. R.: 1999, The Nature and Properties of Soil, 12th edn., Prentice Hall, Upper Saddle River, NJ, U.S.A, 881 pp.
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