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Wetland mitigation is implemented to replace ecosystem functions provided by wetlands; however, restoration efforts frequently fail to establish equivalent levels of ecosystem services. Delivery of microbially mediated ecosystem functions, such as denitrification, is influenced by both the structure and activity of the microbial community. The objective of this study was to compare the relationship between soil and vegetation factors and microbial community structure and function in restored and reference wetlands within a mitigation bank. Microbial community composition was assessed using terminal restriction fragment length polymorphism targeting the 16S rRNA gene (total bacteria) and the nosZ gene (denitrifiers). Comparisons of microbial function were based on potential denitrification rates. Bacterial community structures differed significantly between restored and reference wetlands; denitrifier community assemblages were similar among reference sites but highly variable among restored sites throughout the mitigation bank. Potential denitrification was highest in the reference wetland sites. These data demonstrate that wetland restoration efforts in this mitigation bank have not successfully restored denitrification and that differences in potential denitrification rates may be due to distinct microbial assemblages observed in restored and reference (natural) wetlands. Further, we have identified gradients in soil moisture and soil fertility that were associated with differences in microbial community structure. Microbial function was influenced by bacterial community composition and soil fertility. Identifying soil factors that are primary ecological drivers of soil bacterial communities, especially denitrifying populations, can potentially aid the development of predictive models for restoration of biogeochemical transformations and enhance the success of wetland restoration efforts.
Wetlands provide more ecosystem services (e.g., flood control, water purification, nutrient cycling, and habitat for wildlife) per hectare than any other ecosystem (16). Riparian wetlands, in particular, are sites of intense biogeochemical activity and play an important role in improving water quality, recycling nutrients, and detoxifying chemicals (41). Changing patterns of land use over the last century have resulted in the loss of over half of the wetlands in the contiguous United States (17) and about 60% of wetlands in the Midwestern United States (82). The loss of ecosystem services through conversion of wetlands to alternative (primarily agricultural) land uses exacerbates nutrient pollution and eutrophication of downstream ecosystems (57). Declines in wetland acreage have continued despite a federal policy goal of no-net-loss of wetland acreage and function adopted in 1990 (7, 55). Wetland mitigation projects provide compensation for impacted wetlands and aim to replace the critical functions provided by wetlands. Despite decades of wetland mitigation, however, restoration efforts frequently fail to reestablish desired levels of ecosystem services. Restoration outcomes remain uncertain, and more information is necessary in order to improve monitoring and assessment of wetland development (13, 18, 50, 80).
One approach to wetland compensation is through mitigation banks. These sites are areas that are restored, established, enhanced, or preserved for replacement of wetlands that will be affected by future land use change. Mitigation banks are considered “third-party” compensatory mitigation, where the permittee (e.g., developer planning to destroy a wetland) is responsible for purchasing wetland credits in acreage, but the wetland bank is established and managed by another party (24). Wetland mitigation banks have unique characteristics that distinguish them from smaller individual restoration projects (7, 69, 81). Due to their size, wetland mitigation banks are especially heterogeneous and may have a great deal of within-site variability in hydrology and nutrient status, making it challenging to implement a single restoration design. Thus, wetland mitigation banks require intense management and monitoring for improved success (7, 69, 81).
Restoration efforts such as mitigation banks aim to replace chemical, physical, and biological ecosystem functions of wetlands that have been lost through anthropogenic disturbance (24). Monitoring of wetland mitigation sites has largely focused on measures of macro-scale community structure (e.g., vegetation surveys) (52) along with measures of hydrology and soil type (24). Measurement of vegetation is a common proxy for wetland performance but does not provide an accurate assessment of wetland function (6, 52). Quantitative assessment is achievable, however, for ecosystem services such as water quality improvement through nitrate removal, where well-characterized microbial mechanisms underlie denitrification processes.
The link between microbial community structure and function in a restoration context is a topic of current interest (33). Relating microbial community composition and dynamics to chemical, physical, and biological variables can help to reveal important ecological drivers of microbial communities and their activities (26, 35, 42). Conserved bacterial functional genes related to specific biogeochemical transformations allow evaluation of the community structure of microbial populations directly involved in these processes (49, 60, 63, 77, 79). Assessing the diversity of microorganisms that are specifically involved in denitrification is possible through amplification of the nosZ gene, which encodes the catalytic subunit of nitrous oxide reductase, the enzyme responsible for the final step of denitrification (60, 63, 66). Phylogenetically diverse microorganisms can carry out denitrification though the majority of previously described denitrifiers belong to subphyla within the Proteobacteria (53, 56, 60, 61). Denitrification is a facultative process that occurs only under anaerobic conditions (53, 75). Complete denitrification to N2 is more prevalent in anaerobic, saturated wetland ecosystems (14, 76), and incomplete denitrification to N2O is the less desirable, more common endpoint of denitrification under more aerobic, drier conditions (14, 62). While the environmental factors (e.g., oxygen, carbon, nitrate, and pH) that influence bulk denitrification rates have been well characterized (31, 72), the influence of these factors on the composition of denitrifier communities, particularly in a restoration context, is unclear. Understanding the relationship between the microbial populations responsible for nitrogen transformations and easily measured environmental parameters (e.g., soil chemical and physical measures) could lead to assessment metrics that are linked directly to ecosystem functions such as denitrification and bridge the current gap in functional assessment methods (36, 60, 70).
The objectives of this study were (i) to compare the microbial and plant community composition in restored wetlands to the composition in adjacent reference floodplain forest wetlands; (ii) to assess the relationship between microbial community composition (based on terminal restriction fragment length polymorphism [T-RFLP]) and potential denitrification activity throughout the mitigation bank; and (iii) to examine soil factors correlated with microbial community composition using both phylogenetic and functional gene markers. As soil environmental conditions affect microbial community structure and activity, we expected that sites where wetland hydrology and soil chemistry have been successfully restored would harbor microbial assemblages that are similar in composition and denitrification function to those observed in reference wetlands within this mitigation bank.
Restored wetland sites are located within the 342-ha Morris Wetland Mitigation Bank created by the Illinois Department of Transportation in Morris, IL (Fig. (Fig.1).1). This bank was acquired in 1999 and has been monitored for mitigation purposes since 2004 by the Illinois Natural History Survey (INHS) (10, 25). The goal of this mitigation project is to reestablish a continuous floodplain forest in place of previous agricultural land. Most of the hydric soils in the sampled areas were a Sawmill silt clay loam (fine-silty, mixed, superactive, mesic Cumulic Endoaquolls) formed in alluvium on floodplains (10, 25).
The sampling scheme employed a randomized complete block design with subsamples (Fig. (Fig.1).1). Five replicate sites within the mitigation bank containing characteristic wetland vegetation and hydric soils were designated blocks. Each block contained plots representing each of three wetland types. Within each block, variable topography resulted in locations that were considered “low” elevation and “high” elevation. Low-elevation plots were established in restored wetland areas with wetland hydrology (frequently saturated soil) and were presumed to represent more successfully restored wetlands; high-elevation plots were established in restored wetland areas with less favorable wetland hydrology (presumed to be less successfully restored areas of the mitigation bank). Reference floodplain forest wetland plots were included in each block for comparison to restored sites (Fig. (Fig.11).
Soil sample collection and vegetation surveys were conducted in September 2006 (fall) and May 2007 (spring). In each of the five wetland blocks, data were collected from four random subsamples within each plot representing the three wetland types (low-elevation or high-elevation restored wetlands and reference wetlands) (Fig. (Fig.1).1). For each of the subsamples, herbaceous vegetation was surveyed within a 0.25-m2 quadrat, and plant species cover classes were recorded. Within each quadrat, six soil cores were collected randomly (0- to 12-cm depth using a 1.9-cm diameter corer) and composited (Fig. (Fig.1).1). Soil samples were stored on ice for transport to the laboratory. Samples used for activity analyses were stored at 4°C overnight and processed the next day. Soils intended for molecular microbial analyses were frozen at −20°C until DNA extraction.
In order to evaluate the reducing conditions in the soil, the indicator of reduction in soil (IRIS) approach was used (InMass Technologies Inc., West Lafayette, IN) (11). IRIS tubes (ferrihydrite-coated polyvinyl chloride [PVC] tubes) were installed at two quadrats within each low- and high-elevation restored wetland sample plot and in one quadrat in each reference plot in September 2006 and were removed in May 2007. Digital images were produced from each IRIS tube and transformed to black/white pixels to quantify the loss of ferrihydrite paint from the tube surface, which is used as an assessment of reducing conditions (11). Total area of reduction (percent white pixels) was recorded and averaged for each restored wetland type, resulting in a single value for reduction status for each wetland type (low-elevated restored, high-elevated restored, and reference) at each of the five wetland sites.
Gravimetric soil moisture was determined for each soil sample by calculating the weight of water in a sample divided by the total dry weight of a sample after 24 h at 105°C. A subsample of air-dried soil was ground into a fine powder and analyzed to determine total organic matter (total organic C [TOC] and total N [TN]). Elemental analyses of C and N were completed using combustion methods (ECS 4010; Costech Analytical Instruments, Valencia, CA). The pH of the soil solution (5 g of soil plus 5 ml of deionized water) was determined by averaging three measurements per sample. After addition of 2 M KCl to 5 g of air-dried soil, samples were shaken for 1 h, soil extracts were collected, and available ammonium (NH4+) and nitrate (NO3−) were analyzed using colorimetric analyses based on the Berthelot method (59, 68).
Denitrification potential of the soil microbial community was estimated using the acetylene inhibition method on fresh soil samples collected in May 2007 (64, 73). Denitrification potential was assessed for replicates of each wetland type in all five blocks (n = 15). Soil samples used for the acetylene inhibition assay were combined subsamples from each wetland sample plot. In 125-ml Wheaton bottles, 75 ml of deionized water and 1.3 ml of chloramphenicol (100 mg/ml) were combined, and then soil (25 ml) was added via displacement. The bottles were sealed with septa-centered caps, shaken, purged with He gas for 5 min, and vented prior to the start of the assay. No amendments of C and N were made. Before the acetylene inhibition assay was performed, a pilot study was carried out on a set of wetland soils amended with nitrate, glucose, or both. No significant differences in nitrous oxide production were observed among these controls during the 3-h assay (data not shown), indicating that C and N were not limiting microbial activity in these soils. To equilibrate N2O in aqueous and sediment phases, each bottle was shaken for 5 min before the headspace was sampled at each time point. Gas samples were collected at 0, 1, 2, and 3 h after the start of the assay. Oven-dry mass was determined by drying soil at 105°C following the assay.
Gas samples were analyzed for N2O using a Varian 3600 gas chromatograph ([GC] Varian Inc., Walnut Creek, CA) equipped with a 12-ft Porapak Q80 column and a 63Ni electron capture detector (oven temperature, 70°C; flow rate, 30 ml min−1). Gas standards ranging from 3 parts per million of volume (ppmv) to 78 ppmv N2O were generated from 99% N2O (Grace Divisions, Deerfield, IL). N2O concentrations of each sample per dry mass were plotted against time, and the slope of this line was the denitrification rate (ng of N2O dry mass of g−1 h−1). During the assay, N2O production was linear for the majority of the samples measured. Samples more concentrated than the highest standard were diluted prior to GC analysis.
Total genomic DNA was extracted from freeze-dried soil samples collected from all subsamples representing each wetland plot using a FastDNA SPIN Kit for Soil (MP Biomedicals, Solon, OH). Genomic DNA was further purified using cetyl trimethyl ammonium bromide (CTAB) extraction to remove contaminating humic acids (65). DNA concentration was adjusted to a standard concentration of 10 ng/μl prior to DNA analyses.
Bacterial community composition in wetland soil samples was assessed using T-RFLP (48). PCR to amplify 16S rRNA genes for T-RFLP analysis contained a buffer consisting of 50 mM Tris (pH 8.0), 250 μg of bovine serum albumin per ml, 3.0 mM MgCl2 (catalog number 1770; Idaho Technology, Salt Lake City, UT), 250 μM each deoxynucleoside triphosphate (dNTP), 10 pmol of each primer, 1.25 U of Taq polymerase (Promega, Madison, WI), and 20 ng of extracted DNA in a final volume of 25 μl. The 16S rRNA genes were amplified using primers 8F (5′-AGAGTTTGATCMTGGCTCAG-3′; bacteria-specific 16S rRNA gene) and 1492R (5′-GGYTACCTTGTTACGACTT-3′; universal 16S rRNA gene) (46). The 8F primer was labeled with the phosphoramidite dye 6-carboxyfluorescein (6-FAM).
Reaction mixtures were cycled in an Eppendorf MasterCycler Gradient (Eppendorf, Hauppauge, NY) with an initial denaturation at 94°C for 2 min, followed by 30 cycles of 94°C for 35 s, 55°C for 45 s, and 72°C for 2 min, with a final extension carried out at 72°C for 2 min. PCR products amplified from each sample were digested in single-enzyme restriction digests containing HhaI, MspI, or RsaI.
Denitrifier community composition was also assessed using T-RFLP. The nitrous oxide reductase gene (nosZ) was used to target populations of denitrifiers involved in the transformation of nitrous oxide to dinitrogen gas (60). This subset of denitrifiers mediates the final step in complete denitrification (N2O → N2), and they are key populations for determining a wetland's capacity to mitigate nitrate pollution. PCR reaction mixtures to amplify the nosZ gene, which encodes the catalytic subunit of nitrous oxide reductase, contained 50 mM Tris (pH 8.0), 250 μg of bovine serum albumin per ml, 2.0 mM MgCl2, 200 μM each dNTP, 20 pmol of each primer, 2.5 U of Taq polymerase (Promega, Madison, WI), and 100 ng of extracted DNA in a final volume of 50 μl. The nosZ gene was amplified using nosZ-F-1181 (5′-CGCTGTTCITCGACAGYCAG-3′) and nosZ-R-1880 (5′-ATGTGCAKIGCRTGGCAGAA-3′) to yield a 700-bp PCR product (60). The nosZ reverse primer was labeled with the phosphoramidite dye 6-FAM. Reaction mixtures were cycled with initial denaturation at 94°C for 3 min, followed by 25 cycles of 94°C for 45 s, 56°C for 1 min, and 72°C for 2 min, with a final extension carried out at 72°C for 7 min. A Qiagen MinElute PCR purification kit was used to combine and concentrate the nosZ PCR product from three 50-μl reaction mixtures. PCR products amplified from each sample were digested in single-enzyme restriction digests containing AluI, HhaI, or MboI.
The length and relative abundance of terminal restriction fragments (T-RFs) were determined by denaturing capillary electrophoresis using an ABI 3730xl Genetic Analyzer (Applied Biosystems, Foster City, CA). Electrophoresis conditions were 63°C and 15 kV with a run time of 120 min using the POP-7 polymer. A custom 100- to 2,000-bp rhodamine X-labeled (ROX) size standard (Bioventures, Murfreesboro, TN) was used as the internal size standard for T-RFs generated from 16S rRNA PCR products. An ABI GeneScan ROX 1000 size standard was used as the internal size standard for the nosZ T-RFLP analysis. Size-calling was carried out using GeneMarker, version 1.6 (SoftGenetics, State College, PA). Each terminal restriction fragment represents a microbial population, and the combination of all T-RFs produced from a sample (often termed a “community fingerprint”) was considered to represent the assemblage of microbial populations present in the original soil sample. The signal strength of each T-RF peak was normalized to account for run-to-run variations in signal detection by dividing the area of individual peaks by the total T-RF fluorescence detected in each sample, expressing each peak as a proportion of the observed community (42, 58, 78). Terminal restriction fragments that exceeded a detection threshold of 100 relative fluorescence units were included in community analyses. Output from the three T-RFLP profiles produced from digestion of each PCR product was concatenated prior to statistical analysis.
Correspondence analysis was performed on bacterial community composition based on 16S rRNA and nosZ T-RFLP carried out for all subsamples (60 total) and plant community composition based on vegetation surveys. Environmental parameters available for correspondence analysis included pH, TOC, TN, available NH4+ and NO3−, soil moisture, soil reduction status (IRIS), and potential denitrification rate. The average distance between all samples and the group centroid (mean centroid distance) was calculated from the sample scores on the first two correspondence analysis axes to estimate variability in denitrifier community composition within reference or restored wetlands. Correspondence analyses were carried out using Canoco, version 4.5.1 (Biometrics-Plant Research International, Wageningen, Netherlands) (71).
To statistically compare communities using analysis of similarity (ANOSIM), plant community composition based on percent cover of species and T-RFLP relative fluorescence values for microbial communities were averaged within each replicate wetland plot prior to calculating similarity matrices for the community data. Similarity matrices were generated for plant, 16S rRNA and nosZ T-RFLP data by calculating the Bray-Curtis similarity coefficient for each possible pair of samples (47). For each similarity matrix for each date (fall and spring) and community (plant, 16S rRNA, and nosZ), analysis of similarity was used to test for significant differences in community composition among wetland types (n = 5 replicates for each wetland type) (15). The ANOSIM procedure generates a test statistic, R, calculated based on the following formula: R = (rB − rW)/[1/4n(n − 1)], where n is the total number of samples, rB is the average of rank similarities arising from all pairs of replicates between different wetland types, and rW is defined as the average of all rank similarities among replicates within wetland types. An R value of 1 indicates complete dissimilarity between groups; an R of 0 indicates a high degree of community similarity among wetland types. Calculations of similarity coefficients and ANOSIM were carried out using PRIMER 5, version 5.2.7 (Primer-E Ltd., Plymouth, United Kingdom).
Analysis of variance (ANOVA) was used to compare denitrification potential and soil environmental factors (pH, TOC, TN, C/N, NH4+, NO3−, moisture, and IRIS) among wetland types (n = 5 replicates for each wetland type). In the case where ANOVA assumptions were not met, denitrification potential, available NH4+ and NO3−, and soil moisture were log10 transformed before ANOVA was performed. The ANOVA was performed using the PROC MIXED procedure of SAS (SAS, version 9.1.3; SAS Institute, Cary, NC). The block effect was not significant (P > 0.05) in the initial analysis and, therefore, was not included in the final model. Tukey's posthoc test was carried out to determine between-group differences in denitrification potential or soil environmental factors between wetland types. Stepwise regression was carried out to test the influence of the microbial communities and soil environmental factors on potential denitrification rates using the PROC REG procedure in SAS (SAS, version 9.1.3; SAS Institute, Cary, NC). Total bacterial and denitrifier communities were collapsed into univariate variables based on the sample scores for the first two correspondence analysis axes prior to regression analysis.
Microbial communities from reference wetland sites were compared to communities in adjacent restored wetland sites, which were subdivided into two classes: low elevation (with higher soil moisture and higher probability of anaerobic conditions) and high elevation (with lower potential for reducing conditions) within a mitigation bank (Fig. (Fig.1).1). The average numbers of 16S T-RFs observed (for all digests combined) were 256, 214, and 195 for low-elevation, high-elevation, and reference wetlands, respectively. The average numbers of nosZ T-RFs observed (from all digests) were 63, 47, and 72 for low-elevation, high-elevation, and reference wetlands, respectively. Bacterial community composition in the reference floodplain forest was significantly different from that in communities observed in the restored sites (both low and high elevation) in fall (ANOSIM R values of 0.724 and 0.728 for comparisons of samples from low- and high-elevation restored wetlands, respectively, with those from reference wetlands; P of 0.008). In contrast, bacterial assemblages present in the two classes of restored wetlands could not be distinguished (ANOSIM R of 0; P of 0.059) (Table (Table11 and Fig. Fig.2A).2A). Similar patterns in community composition among classes of wetlands were observed in spring. Again, there was little distinction in total bacterial communities between the two types of restored wetlands (ANOSIM R of 0.272; P of 0.016) but strong and significant differences between each class of restored wetlands and the reference sites (ANOSIM R values of 0.680 and 0.668 and P of 0.008, for comparisons of reference wetland communities with low- and high-elevation sites, respectively) (Table (Table11 and Fig. Fig.2B).2B). Seasonal variation in microbial communities was also observed (data not shown), but the spatial patterns in microbial community composition were apparent in each season (Fig. (Fig.22 and and3).3). Denitrifier communities were very similar among the replicate plots located within reference floodplain forest wetlands, and these populations showed less among-plot variability than denitrifiers in restored wetlands (mean centroid distances for fall, 0.303 for the reference wetlands versus 0.486 for restored wetlands; for spring, 0.279 for reference versus 0.485 for restored wetlands) (Fig. (Fig.3).3). Denitrifier assemblages in reference wetlands showed very low variability across replicate sampling plots (Fig. (Fig.3),3), suggesting that habitat filtering by the reference wetland soil environment has consistently resulted in a denitrifier assemblage that is characteristic of floodplain forest wetlands in this mitigation bank. The greatest difference in denitrifier community composition was observed between high-elevation restored and reference wetlands in fall (ANOSIM R of 0.708; P of 0.008). Denitrifier assemblages were less distinct between low-elevation restored plots and reference wetlands (ANOSIM R of 0.360; P of 0.024), suggesting that the high soil moisture, organic matter, and available nitrogen in low- compared to high-elevation restored wetlands are leading to development of denitrifier populations similar to those seen in reference wetlands (Table (Table22 and Fig. Fig.3).3). Microorganisms vary in tolerance to soil moisture, and these differences can directly influence community composition (1, 43). However, soil moisture and its subsequent influence on redox conditions are not the only controls on denitrifier activity. Carbon availability and pH can also be important factors influencing microbial activity (12, 75).
Patterns in plant community composition corresponded to those observed for total bacterial community composition; for both plants and bacteria, distinctly different communities were observed in restored and reference wetlands in the mitigation bank (Fig. (Fig.22 and and4).4). Plant communities in the low- and high-elevation restored wetland plots were distinctly different from those in reference wetlands (comparisons of plant communities in low-elevation restored versus reference wetlands generated ANOSIM R values of 0.682 and 0.716 for samples collected in fall and spring, respectively, with a P of 0.008; comparisons of plant communities in high-elevation restored versus reference wetlands generated ANOSIM R values of = 0.926 and 0.772 for samples collected in fall and spring, respectively, with a P of 0.008) (Fig. (Fig.4).4). Hydrophytic trees and shrubs were planted in restored wetlands (25), but development of these plantings into forested wetland communities will take time (50). The current differences observed in plant community composition reflect recent restoration activities and the lack of a mature forest canopy in the restored wetlands. Carbon additions by various plant species can directly impact microbial community decomposition rates and soil organic matter accumulation over time, thus affecting microbial community composition and activity (2).
Denitrification potential was significantly higher in the reference than restored floodplain forest wetlands (by ANOVA, df of 11, F of 20.56, and P of 0.0002; by Tukey's posthoc test of low elevation versus reference, df of 11, F of 11.70, and P of 0.0057; for high elevation versus reference, df of 11, F of 41.09, and P < 0.0001) (Table (Table2).2). Significantly higher denitrification potential was observed in the low-elevation restored wetlands than in the high-elevation plots (df of 11, F of 10.06, and P of 0.0089) (Table (Table2).2). The low-elevation restored wetlands had higher soil moisture (Table (Table2),2), which is more conducive to formation of anaerobic microsites that are permissive for denitrification. Soil moisture and surface hydrology were identified as important factors for supporting high denitrification activity in previous studies (32, 38, 54). In the present study, high denitrification activity was characteristic of microbial communities in the reference wetlands compared to restored sites (Table (Table22 and Fig. Fig.22 and and3).3). The potential denitrification rate was influenced by the overall bacterial community composition and soil fertility. We found that bacterial community composition accounted for 40% of the variation, and nitrate, ammonium, C/N ratio, and pH accounted for about 32% of the variation in denitrification potential (Table (Table33).
Microbial populations capable of denitrification targeted by the nosZ gene are commonly detected among different habitats (53, 60, 61, 75). Denitrifier populations can vary greatly in their physiology and demonstrate variable responses to environmental gradients, allowing the soil environment to influence the activity, abundance, and community structure of the denitrifiers (20, 56, 75, 84). Thus, the soil environment will influence rates of denitrification proximally through its influence on microbial physiology (e.g., anaerobic conditions) and ultimately through shaping the composition of the microbial community. Both mechanisms were potentially occurring in the present study. The limited variation in denitrifier assemblages in reference wetlands throughout the mitigation bank (Fig. (Fig.3)3) indicates that the soil environment in these ecosystems may have strongly influenced the composition of the microbial community, and characteristic wetland soil conditions throughout the reference wetland sites support assemblages of denitrifiers with similar structure and function. While denitrifier assemblages in some restored wetland sites resembled reference wetland denitrifier communities (Fig. (Fig.3),3), restored and reference wetland soils did not demonstrate equivalent denitrification activities (Table (Table2).2). The potential denitrification rate was mainly influenced by the overall composition of the bacterial community and soil fertility (nitrate, ammonium, C/N ratio, and pH) (Table (Table33).
Prior to agricultural land use of the restored areas, the study site was historically floodplain forest wetland (10, 25). Differences between reference and restored wetland plots could have resulted from the land use change that led to variation in hydrology over time, and the relic soils at this mitigation bank are no longer subject to the historical wetland hydrology (10, 25). From a restoration context, it is important to recognize the capacity for denitrifier populations to effectively carry out functions and to understand the influence of local soil factors on these dynamic communities.
Restoration of wetland ecosystem services depends on functional redundancy among microbial populations or on multiple microbial populations possessing the capacity for denitrification. Functional redundancy has been previously demonstrated to play a role in maintenance of microbial processes among different communities (5, 34, 60, 61, 77), but previous studies have noted that microbial taxa can vary in response to environmental stresses, such as those related to land use change, potentially impacting microbial activity (12, 67). We used T-RFLP to detect distinct patterns in community composition that correspond to distinct differences in denitrification among restored and reference wetlands (Fig. (Fig.22 and and3;3; Tables Tables11 and and22).
During Fall 2006, soil moisture, total organic carbon, total nitrogen, C/N ratio, and available ammonium and nitrate were higher in reference than in restored wetlands (Table (Table2).2). In Spring 2007, similar trends were observed in the soil properties measured; however, no differences were detected in available ammonium (Table (Table2).2). Higher levels of soil moisture, pH, total organic matter (TOC), soil C/N ratio, and available nitrate (NO3−) along correspondence analysis (CA) axis 1 were characteristic of reference wetland denitrifier communities (Fig. (Fig.3A).3A). During both seasons, the greatest difference in bacterial community structure between the restored and reference wetland types was displayed along CA axis 1 (Fig. (Fig.2).2). This axis was positively correlated with levels of moisture, soil organic matter (TOC and TN), and available nitrate (NO3−) (Fig. (Fig.2),2), indicating that these measures vary significantly among the restored and reference wetlands (Table (Table2).2). In addition, lower C/N values were characteristic of restored wetland sites (Fig. (Fig.2).2). Significant differences in soil moisture and soil fertility between reference and restored wetlands were associated with differences in overall bacterial and denitrifier community structure among natural and restored wetlands (Table (Table22 and Fig. Fig.22 and and3).3). Denitrification was influenced by the composition of the bacterial community and available inorganic N (Table (Table3).3). The physiologies of microbial populations responsible for wetland water quality functions are strongly affected by redox conditions, which are influenced by the water regime (33). In addition, changes in substrate availability, measured in soil fertility status, can directly influence microbial community structure and activity (33, 79). This argues that functional redundancy cannot be relied upon to restore the nitrate removal function of this restored floodplain forest.
Despite the land use conversion from agriculture back to floodplain forest, the wetland soil environment has not been restored (Table (Table2),2), and significant differences in microbial and plant community assemblages between reference and restored wetlands reflect the distinct soil habitats (Fig. (Fig.2,2, ,3,3, and and4).4). The legacy of past land use may be preserved in a number of chemical, physical, and biological aspects of an ecosystem and may have consequences for ecosystem management and restoration efforts (3, 23, 28-30, 44).
Land use change alters the spatial distribution of soil nutrients, affecting both plant and microbial community composition (27, 29). Land use change can have significant and long-term effects on the soil environment by influencing parameters such as fertility, hydrology, redox status, and biodiversity. These changes will affect microbial community structure and function, both directly and indirectly (3, 21, 27, 37, 67). Microbial populations differ in their sensitivities to land use change; thus, past land use may have lasting consequences for the composition and activity of soil microbial communities. The microbial community data generated in the current study shows evidence of this legacy effect. Presuming that soil conditions (and microbial communities) would have been similar throughout the natural wetland area that was once on the site of this mitigation bank (as we see in the replicate reference sites within each block) (Fig. (Fig.1,1, ,2,2, and and3),3), the distinction in overall microbial community composition between the reference and restored sites may result from lingering effects of prior agricultural land use (Table (Table22 and Fig. Fig.2).2). Supporting this idea was the observation that despite differences in moisture and soil chemistry between the two classes of restored wetlands (Table (Table2),2), microbial assemblages in restored sites were not readily distinguished by analyses based on the rRNA operon or nosZ gene (Table (Table1;1; Fig. Fig.22 and and33).
Legacy effects from prior land use can have irreversible impacts on the microbial community composition and activity, making restoration of nitrate removal processes challenging (13, 19, 27, 83). Prior land use may have strongly constrained restoration of denitrification in this mitigation bank even though some restored areas were inundated with water. Previous studies have demonstrated that the microbial community structure changes in response to acute disturbances, but rates of measured functions remain stable because of redundancy in microbial populations capable of the function of interest (4, 45, 51, 77). In this study, microbial communities demonstrated the potential for redundancy as denitrifier populations were detected in all samples. However, potential denitrification rates were significantly lower in the restored wetlands, indicating that present environmental conditions or legacy effects from prior land use constrain microbial activity even when the potential for the microbial function exists. Differences in denitrifier abundance may also explain differences in denitrification activity; however, quantification of the nosZ gene was not assessed in this study. Land use change can modify soil fertility or hydrology, resulting in long-lasting impacts on plant or microbial community composition (9, 27, 29, 39, 74). In this study, higher soil moisture and fertility measurements characterized natural wetland areas able to support a distinct denitrifier community exhibiting higher activity than adjacent restored wetlands.
Design and monitoring of wetland mitigation banks have been challenging and must be refined to ensure effective delivery of wetland ecosystem services (7, 69, 81). Since wetland mitigation credits are sold once the project goals for the mitigation bank are met, these sites may require intense planning and monitoring (compared to individual mitigation sites) in order to achieve functioning wetlands in a reasonable time frame. It is important to assess mitigation banks differently and more thoroughly, especially because of the size and heterogeneity of the area (8, 69). Assessment protocols linked to ecological drivers of wetland microbial communities and their processes are needed to ensure successful delivery of ecosystem services by mitigation banks. Along with hydrology, our results indicate that fertility (e.g., nitrate and carbon availability) is an important indicator of the capacity of wetland soils to support resident microbial communities and denitrifying activity (20, 22, 40). Microorganisms are responsible for driving nutrient cycling, and understanding their dynamics in response to wetland mitigation activities can offer insight into appropriate management and monitoring of restored areas (33, 79). Successful restoration of denitrification may be possible if environmental conditions are appropriately restored.
The Morris Wetland Mitigation Bank was restored by the Illinois Department of Transportation. D. N. Flanagan provided technical assistance in the lab and field, and M. A. Feist provided logistical assistance in the field. J. C. Castro provided assistance on statistical analyses. E. W. Wheeler and A. C. Yannarell contributed helpful comments on the manuscript.
This material is based upon work supported by the Cooperative State Research, Education and Extension Service, U.S. Department of Agriculture, under project number ILLU 875-374. This research was also supported in part by the Program in Ecology, Evolution, and Conservation Biology at the University of Illinois at Urbana-Champaign.
Published ahead of print on 7 May 2010.