JEQ Journal of Natural Resources and Life Sciences Education
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Published online 27 June 2007
Published in J Environ Qual 36:1172-1180 (2007)
DOI: 10.2134/jeq2006.0462
© 2007 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF) Free
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Mayer, P. M.
Right arrow Articles by Canfield, T. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Mayer, P. M.
Right arrow Articles by Canfield, T. J.
Agricola
Right arrow Articles by Mayer, P. M.
Right arrow Articles by Canfield, T. J.
Related Collections
Right arrow Ecosystem Management
Right arrow Best Management Practices
Right arrow Ground Water Quality

Meta-Analysis of Nitrogen Removal in Riparian Buffers

Paul M. Mayer*, Steven K. Reynolds, Jr., Marshall D. McCutchen and Timothy J. Canfield

USEPA, Office of Research and Development, National Risk Management Research Lab., Ground Water and Ecosystems Restoration Div., 919 Kerr Research Dr., Ada, OK 74821. S.K. Reynolds, Jr., current address, Dep. of Biology, Lake Erie College, 391 W. Washington St., Painesville, OH 44077. M.D. McCutchen, current address, Homer L. Dodge Dep. of Physics and Astronomy, Univ. of Oklahoma, 440 W. Brooks St., Norman, OK 73019

* Corresponding author (mayer.paul{at}epa.gov)

Received for publication October 24, 2006.

   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Riparian buffers, the vegetated region adjacent to streams and wetlands, are thought to be effective at intercepting and reducing nitrogen loads entering water bodies. Riparian buffer width is thought to be positively related to nitrogen removal effectiveness by influencing nitrogen retention or removal. We surveyed the scientific literature containing data on riparian buffers and nitrogen concentration in streams and groundwater to identify trends between nitrogen removal effectiveness and buffer width, hydrological flow path, and vegetative cover. Nitrogen removal effectiveness varied widely. Wide buffers (>50 m) more consistently removed significant portions of nitrogen entering a riparian zone than narrow buffers (0–25 m). Buffers of various vegetation types were equally effective at removing nitrogen but buffers composed of herbaceous and forest/herbaceous vegetation were more effective when wider. Subsurface removal of nitrogen was efficient, but did not appear to be related to buffer width, while surface removal of nitrogen was partly related to buffer width. The mass of nitrate nitrogen removed per unit length of buffer did not differ by buffer width, flow path, or buffer vegetation type. Our meta-analysis suggests that buffer width is an important consideration in managing nitrogen in watersheds. However, the inconsistent effects of buffer width and vegetation on nitrogen removal suggest that soil type, subsurface hydrology (e.g., soil saturation, groundwater flow paths), and subsurface biogeochemistry (organic carbon supply, nitrate inputs) also are important factors governing nitrogen removal in buffers.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
THE USEPA considers nitrogen one of the primary stressors in aquatic ecosystems (USEPA, 2002a). Though nitrogen is an important nutrient for all organisms, excess nitrogen is a pollutant that causes eutrophication in surface water and contaminates groundwater (Carpenter et al., 1998). Streams receive chronic nitrogen inputs in various chemical forms such as nitrate (NO3–), ammonia (NH3), and organic N from upland sources such as fertilizers, animal wastes, leaf litter, leaking sewer lines, atmospheric deposition, and highways (Carpenter et al., 1998; Swackhamer et al., 2004). Subsequent eutrophication leads to environmental impacts such as toxic algal blooms, oxygen depletion, fish kills, and loss of biodiversity (Vitousek et al., 1997).

Nitrogen enters aquatic ecosystems in various forms through multiple pathways. For example, nitrous oxides (NOX) enter by atmospheric deposition, whereas NO3– often enters through groundwater and particulate nitrogen in the form of plant litter and other detritus follows terrestrial routes. NO3– is of particular concern as an environmental stressor because it is biologically reactive, poses a human health risk (i.e., methemoglobinemia; USEPA, 2002b), and often is found in groundwater (Welch, 1991).

Riparian buffers are thought to be an effective, sustainable means of protecting aquatic ecosystems against anthropogenic inputs of nitrogen (Phillips, 1989; Verhoeven et al., 2006) in which nitrogen species may be transformed by various processes including plant uptake, microbial immobilization, soil storage, and groundwater mixing (Lowrance et al., 1997) and denitrification, a microbially mediated transformation of NO3– to N2, a gas phase of nitrogen (Korom, 1992). Denitrification removes nitrogen from a system, whereas other biological processes such as uptake by plants eventually return nitrogen to the system through senescence and microbial decay.

Establishing riparian buffers often is considered a best management practice (BMP) by state and federal resource agencies for maintaining water quality (NRCS, 2003; Bernhardt et al., 2005b). Buffer effectiveness depends on buffer ability to intercept and attenuate nitrogen traveling along surface or subsurface pathways. The extent to which riparian buffers attenuate nitrogen and subsequently improve water quality is thought to be a function of buffer width in concert with landscape and hydrogeomorphic characteristics (Vidon and Hill, 2004). By some estimates, the width of a buffer accounts for about 80% of that buffer's nitrogen removal effectiveness (Phillips, 1989). Intuitively, larger and wider riparian buffers should transform and remove more nitrogen from the water. Therefore, numerous State and Federal agencies have guidelines recommending buffers of minimum width to protect stream ecosystems from nutrient inputs (Belt et al., 1992; Christensen, 2000; Lee et al., 2004; Mayer et al., 2005). However, the specific mechanisms responsible for removing nitrogen within buffers are not thoroughly understood. Furthermore, existing information about buffer effectiveness is not synthesized in a practical form and may not be widely distributed to resource managers (Hickey and Doran, 2004). Moreover, managers do not typically have the available resources to assess the effectiveness of site-specific buffers. The purpose of this article is to identify trends in the relations between nitrogen removal capacity and buffer width, as well as hydrological flow path and vegetative cover, extracted from peer-reviewed studies containing empirical data on buffer effectiveness. While we do not provide specific recommendations for buffer width, this meta-analysis of current literature is meant to provide a baseline from which management decisions about riparian buffers can be made in the context of nitrogen attenuation.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Riparian buffers are defined as the zone of vegetation adjacent to streams, rivers, or wetlands (i.e., Lee et al., 2004). For this article, riparian buffer, riparian zone, buffer strip, filter strip, and vegetated filter strip are considered synonyms. We employed database search engines (e.g., Cambridge Abstracts, Google Scholar, etc.) and existing bibliographies (e.g., Correll, 2003) to locate riparian buffer zone literature. We used search terms singly or combination including: riparian, buffer, width, filter strip, vegetated filters, nitrogen, etc. We summarized the results and conclusions from peer-reviewed research papers that contained original data quantifying the effects of riparian buffer width on nitrogen attenuation. Papers that did not relate nitrogen removal to buffer width were not included in the results. Data presented in proceedings and other non-peer-reviewed sources were not included in our meta-analysis.

We calculated nitrogen removal effectiveness in two ways. First, as a percentage based on (i) the percent difference in nitrogen concentration between the influent into and effluent out of the riparian buffer, (ii) percent difference in nitrogen concentration between the terminus of the control buffer and that of the test buffer, or (iii) if recalculation were impossible based on available data, the values presented by the authors were used directly (Appendix 1). We did not distinguish among nitrogen forms when calculating effectiveness as a percentage.

Because NO3– was the form of nitrogen most often measured among studies, we also calculated buffer effectiveness as the mean mass of nitrate nitrogen removed in riparian zones per unit distance where authors provided information on influent and effluent concentrations.

Removal effectiveness as a percentage was plotted against buffer width. Linear and nonlinear regression models were fitted to the data to reveal patterns of nitrogen removal based on width. All buffers included in studies for which efficiencies could be calculated were included in the meta-analyses as independent data points.

We grouped studies by vegetation cover type (forest, forested wetland, wetland, herbaceous, herbaceous/forest mix) and by hydrologic flow conditions (e.g., surface vs. subsurface), factors that may influence nutrient attenuation in riparian buffer zones. We then plotted effectiveness against buffer width by these groups.

We also grouped studies by buffer width category (0–25, 26–50, and >50 m, respectively). We chose these categories based on current state recommendations for minimum buffer widths which currently range from 15.5 to 24.2 m (Mayer et al., 2005). Therefore our three width categories include buffers that are as wide as current recommendations (0–25 m), those twice as wide (26–50 m), and buffers much wider than recommended (>50 m). We then analyzed effectiveness (percentage nitrogen removal and nitrate removal per unit length) among buffer factor groups (width category, flow path, and vegetation type) using non-parametric tests because the dependent variables were not normally distributed (Shapiro–Wilk test for normality, P < 0.001). All analyses and model fitting were performed with Systat 11.0, Sigma Stat 3.1, and SigmaPlot 9.0 software (SSI, 2004).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Buffer Effectiveness
Overall Patterns
We analyzed data from 89 individual riparian buffers from 45 published studies. Nitrogen removal effectiveness varied widely among studies (Appendix 1). Removal effectiveness at one site was calculated as –258% (Appendix 1), due apparently to very low influent (0.12 mg L–1) and effluent (0.43 mg L–1) nitrate concentrations, and was removed from further analysis as an outlier. The remaining data showed that overall, buffers were effective at removing large proportions of the nitrogen from water flowing through riparian zones (mean % ± 1 standard error [SE]: 67.5 ± 4.0, N = 88; Table 1).


View this table:
[in this window]
[in a new window]

  		Table 1. Percent effectiveness of riparian buffers at removing nitrogen. Buffer widths necessary to achieve a given percent effectiveness (50, 75, 90%) are approximate values predicted by the nonlinear model, y = axb. Effectiveness was not predicted (np) for models with R2 Values ≤ 0.2 except for "all studies" model.

 
A small but significant proportion of the variance in removal of nitrogen was explained by buffer width (R2 = 0.09, P = 0.005, N = 88; Fig. 1, Table 1). That is, wider buffers tended to remove more nitrogen, but other factors must also have affected effectiveness. Overall, exponential models (y = axb) were the simplest models that best fit the effectiveness to buffer relationships. Accordingly, 50, 75, and 90% removal efficiencies were estimated to occur among all buffers approximately 4, 49, and 149 m wide, respectively (Fig. 1, Table 1). These estimates had large variances based on SE of the regression models (Table 1).


Figure 1
View larger version (18K):
[in this window]
[in a new window]

  		Fig. 1. Relationships of nitrogen removal effectiveness to riparian buffer width over all studies and analyzed by water flow path. Lines are fitted to model y = axb.

 
Buffer Width Category
Effectiveness was not related to buffer width when analyzing buffers within width categories (P > 0.5, Table 1), suggesting that any effect of buffer width on nitrogen removal occurs only after buffer size reaches a width threshold. This suggestion is supported by the observation that effectiveness differed among buffer width categories (Kruskal–Wallis H = 10.3, df = 2, P = 0.006; Fig. 2, Table 1). Nitrogen removal effectiveness of buffers >50 m wide was greater than that of buffers 0 to 25 m, whereas effectiveness of buffers 26 to 50 m did not differ from the other categories (Dunn's method of multiple comparisons Q = 3.0, P < 0.05; Fig. 2, Table 1). Thus, wider buffers are likely to be more efficient zones of nitrogen removal than narrower buffers.


Figure 2
View larger version (17K):
[in this window]
[in a new window]

  		Fig. 2. Nitrogen removal effectiveness in riparian buffers by buffer width category. Bars represent means ± 1 standard error. Mean ranks of width categories differ if denoted by different letters (Kruskal–Wallis one-way analysis of variance on ranks with Dunn's method of multiple comparisons, P < 0.05).

 
Surface versus Subsurface Flow
Nitrogen removal effectiveness also differed by flow pattern. Subsurface removal of nitrogen was much more efficient than surface removal (Mann–Whitney U = 1247.5, df = 1, P < 0.001; Fig. 3, Table 1). Furthermore, subsurface removal of nitrogen did not appear to be related to buffer width (R2 = 0.02, P = 0.3; Fig. 1, Table 1), whereas a small but significant proportion of the variance in surface removal of nitrogen was explained by buffer width (R2 = 0.21, P = 0.03; Fig. 1, Table 1). That is, wider buffers removed more nitrogen in surface runoff. While some narrow buffers (<15 m) removed significant proportions of nitrogen, six studies (three surface and three subsurface flow) found that narrow buffers actually contributed nitrogen to riparian zones (i.e., had negative effectiveness values; Appendix 1; Fig. 1). Such cases are likely to be short-term events due to nitrification or high rainfall events that lead to rapid inputs of nitrogen (Dillaha et al., 1988; Magette et al., 1989; Sabater et al., 2003). Based on the model y = axb, 50, 75, and 90% nitrogen removal efficiencies in surface flow were estimated to occur in buffers approximately 27, 81, and 131 m wide, respectively (Fig. 1, Table 1). These models also had large associated variances (SE; Table 1).


Figure 3
View larger version (15K):
[in this window]
[in a new window]

  		Fig. 3. Nitrogen removal effectiveness in riparian buffers by water flow path. Bars represent means ± 1 standard error. Mean ranks of flow paths differ if denoted by different letters (Mann–Whitney U test on ranks, P < 0.001).

 
Vegetation Type
Overall nitrogen removal effectiveness did not vary by buffer vegetation type (Kruskal–Wallis H = 6.9, df = 4, P = 0.14; Fig. 4 and Table 1) suggesting that all buffers were equally effective at removing nitrogen. Forested, forested/wetland, and wetland buffers showed no relationship between buffer width and nitrogen removal effectiveness; however, effectiveness of herbaceous and herbaceous/forested buffers increased with width (Fig. 5, Table 1). Based on the model y = axb, nitrogen removal efficiencies of 50, 75, and 90% were estimated for herbaceous buffers approximately 17, 51, and 84 m wide and for herbaceous/forest buffers approximately 3, 18, and 44 m wide, respectively (Table 1). Models had large variances (SE; Table 1). Four herbaceous and two forested buffers added to nitrogen loads where buffers were <15 m (Fig. 5). In such cases, nitrification or high rainfall events may lead to short-term and/or rapid inputs of nitrogen (Sabater et al., 2003).


Figure 4
View larger version (22K):
[in this window]
[in a new window]

  		Fig. 4. Nitrogen removal effectiveness in riparian buffers by buffer vegetation type. Bars represent means ± 1 standard error. Mean ranks of vegetation types do not differ (Kruskal–Wallis one-way analysis of variance on ranks, P = 0.14).

 

Figure 5
View larger version (18K):
[in this window]
[in a new window]

  		Fig. 5. Relationships of nitrogen removal effectiveness to riparian buffer width analyzed by vegetation type. Lines are fitted to model y = axb. Only the regression lines for herbaceous and herbaceous/forest vegetation types are shown because model results for other vegetation types were not significant (P > 0.3).

 
Mass Removal of Nitrate Nitrogen
We analyzed data from 60 riparian buffers for which influent and effluent nitrate nitrogen concentrations were available. Similar to percent removal effectiveness, mass removal of nitrate nitrogen per unit length varied widely among studies. Overall, buffers removed nitrate nitrogen at a rate of (mean ± 1 SE) 0.394 ± 0.084 mg L–1 m–1. Unlike effectiveness, nitrate nitrogen removal did not differ among width categories (Kruskal–Wallis H = 4.8, df = 2, P = 0.09; Table 2), suggesting that nitrate removal rate remained constant across the entire length of buffers.


View this table:
[in this window]
[in a new window]

  		Table 2. Mass removal of nitrate nitrogen in riparian buffers.

 
Nitrate removal was not related to flow pattern (Mann–Whitney U = 256.0, df = 1, P = 0.11; Table 2). Nitrate removal also was not related to buffer vegetation type (Kruskal–Wallis, df = 4, H = 7.3, P = 0.12; Fig. 6, Table 2).


Figure 6
View larger version (19K):
[in this window]
[in a new window]

  		Fig. 6. Mass of nitrate nitrogen removed in riparian buffers by buffer vegetation type. Bars represent means ± 1 standard error. Mean ranks of vegetation types do not differ (Kruskal–Wallis one-way analysis of variance on ranks, P = 0.12).

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
CONCLUSIONS
 REFERENCES
 
Our meta-analysis suggests that wider buffers tend to be more effective at removing nitrogen. Low R2 values of the overall regression analysis suggest that factors other than buffer width influence buffer effectiveness such as (i) vegetation and depth of the root zone where plants can take up nitrogen (Asmussen et al., 1979; Cooper, 1990), and (ii) hydrological flow paths that favor microbial denitrification (i.e., saturated anaerobic soils, adequate carbon supplies, floodplain connections; Dillaha et al., 1989; Simmons et al., 1992; Hanson et al., 1994; Speiran et al., 1998; Leeds-Harrison et al., 1999; Sloan et al., 1999; Hill et al., 2000, 2004; Steinhart et al., 2001; Schade et al., 2001, 2002; Groffman et al., 2003, 2005; Sabater et al., 2003; Richardson et al., 2004). Furthermore, buffer width was not a factor affecting nitrogen removal effectiveness within buffer width categories, indicating that trends in effectiveness are evident only across a broader range of buffer size. Yet, mean nitrogen removal effectiveness in buffers >50 m wide was significantly higher than in narrow buffers (0–25 m), suggesting that buffer width is an important consideration for nitrogen management in watersheds.

Overall, suburface nitrogen removal is more efficient than removal through surface flow. Furthermore, subsurface nitrogen removal may be more directly influenced by soil type, watershed hydrology (e.g., soil saturation, groundwater flow paths, etc.), and subsurface biogeochemistry (organic carbon supply, high NO3– inputs) through cumulative effects on microbial denitrification activity than on buffer width per se. Surface flows bypass zones of denitrification, and thus effectively remove nitrogen only when buffers are wide enough and have adequate vegetation cover to control erosion and filter movement of particulate forms of nitrogen. Herbaceous buffers, for example, may be better at intercepting particulate nitrogen in the sediments of surface runoff by reducing channelized flow. Based on a limited data set fitted to a log-linear model, Oberts and Plevan (2001) found that NO3– retention in wetland buffers was positively related to buffer width (R2 values ranged from 0.35–0.45). Nitrogen removal efficiencies of 65 to 75% and 80 to 90% were predicted for wetland buffers 15 and 30 m wide, respectively, depending on whether NO3– was measured in surface or subsurface flow (Oberts and Plevan, 2001).

Our meta-analysis suggests that vegetation type has a limited impact on buffer effectiveness (Table 1). Only buffers with herbaceous vegetation were more effective when wider (Table 1). However, buffer width may indirectly affect factors promoting denitrification. For example, narrow buffers that produce little vegetative biomass may not provide sufficient stocks of organic material for microbial denitrifiers.

Regardless of width, buffer integrity should be protected against (i) soil compaction (e.g., vehicles, livestock, and construction of impervious surfaces) that might inhibit infiltration or disrupt water flow patterns (Dillaha et al., 1989; NRC, 2002), (ii) excessive leaf litter removal or alteration of the natural plant community (e.g., raking, tree thinning, introduction of invasive species) that might reduce carbon-rich organic matter from reaching the stream, and (iii) practices that might disconnect the stream channel from the flood plain (i.e., urbanization, channelization, bank erosion, stream incision, hard drainage surfaces, and drain tiles) and thereby reduce the spatial and temporal extent of soil saturation (Paul and Meyer, 2001; Groffman et al., 2003, 2005).


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
REFERENCES
 
Based on our meta-analysis, riparian buffers of various types are effective at reducing nitrogen in riparian zones, especially nitrogen flowing in the subsurface. Our study shows that, while some narrow buffers (0–25 m) remove nitrogen, wider buffers (>50 m) more consistently removed significant portions of nitrogen probably by providing more area for root uptake of nitrogen (Asmussen et al., 1979; Cooper, 1990) or more sites where groundwater conditions favor denitrification (Hanson et al., 1994; Leeds-Harrison et al., 1999; Sloan et al., 1999; Hill et al., 2000, 2004; Schade et al., 2001, 2002; Steinhart et al., 2001; Sabater et al., 2003; Richardson et al., 2004). Maintaining buffers around stream headwaters (Peterson et al., 2001; Richardson et al., 2004; Bernhardt et al., 2005a; Bernot and Dodds, 2005) will likely be most effective at maintaining overall watershed water quality while restoring degraded riparian zones, and stream channels may improve nitrogen removal capacity (Groffman et al., 2005). However, because streams and riparian zones have limited capacity to process nitrogen, watershed nutrient management efforts also must include control and reduction of point and nonpoint sources of nitrogen from atmospheric, terrestrial, and aquatic inputs. Furthermore, overtaxing the nutrient removal capacity of riparian zones and floodplain wetlands may lead to losses of biodiversity and production of nitrous oxides (Verhoeven et al., 2006). Establishing a network of buffers adequate to maintain watershed water quality will be dependent on local and centralized conservation activities as well as government regulations and standards (Mayer et al., 2005; Verhoeven et al., 2006).

Appendix 1. Summary table of riparian buffer effectiveness at removing nitrogen (N) by vegetation type, hydrologic flow path, buffer width, and soil type.
NO3– Concentration
Vegetation type
 Flow path
 Buffer width
 N form
 Mean influent
 Mean effluent
 Nitrogen removal effectiveness
 NO3–removed
 Study
m mg L–1 % mg L–1 m–1
Herbaceous surface 4.6 Total N – – –15 – Magette et al. (1989)
Herbaceous surface 9.2 Total N – – 35 – Magette et al. (1989)
Herbaceous surface 7.5 Total N 68 44 35 – Schmitt et al. (1999)
Herbaceous surface 15 Total N 68 33 51 – Schmitt et al. (1999)
Herbaceous surface 4.6 NO3– 1.86 2.37 –27 –0.11 Dillaha et al. (1988)
Herbaceous surface 9.1 NO3– 1.86 2.13 –15 –0.03 Dillaha et al. (1988)
Herbaceous surface 4.6 NO3– – – 27 – Dillaha et al. (1989)
Herbaceous surface 9.1 NO3– – – 57 – Dillaha et al. (1989)
Herbaceous surface 91 Total N 21.6 13.3 38 – Zirschky et al. (1989)
Herbaceous surface 27 NO3– 0.37 0.34 8 <0.01 Young et al. (1980)
Herbaceous surface 26 NH3 3.61 3.05 16 – Schwer and Clausen (1989)
Herbaceous surface 26 TKN 48.9 11.76 76 – Schwer and Clausen (1989)
Herbaceous surface 7.1 NO3– – – 51 – Lee et al. (2003)
Herbaceous surface 13 NO3– – – 51 – Bingham et al. (1980)
Herbaceous surface 33.4 NO3– – – 89 – Bingham et al. (1980)
Herbaceous surface 26 NO3– – – 88 – Bingham et al. (1980)
Herbaceous subsurface 40 NO3– 0.35 0.23 34 <0.01 Sabater et al. (2003)
Herbaceous subsurface 60 NO3– 1.7 0.14 92 0.03 Sabater et al. (2003)
Herbaceous subsurface 20 NO3– 12.42 0.30 98 0.61 Sabater et al. (2003)
Herbaceous subsurface 10.5 NO3– 0.08 0.13 –63 –0.01 Sabater et al. (2003)
Herbaceous subsurface 15 NO3– 11.56 7.34 37 0.28 Sabater et al. (2003)
Herbaceous subsurface 15 NO3– 12.35 2.79 77 0.64 Sabater et al. (2003)
Herbaceous subsurface 25 NO3– 15.5 6.2 60 0.37 Vidon and Hill (2004)
Herbaceous subsurface 70 NO3– 1.55 0.32 80 0.02 Martin et al. (1999)
Herbaceous subsurface 39 NO3– 16.5 3 82 0.35 Osborne and Kovacic (1993)
Herbaceous subsurface 25 NO3– 12.15 1.92 84 0.41 Hefting and de Klein (1998)
Herbaceous subsurface 16 NO3– 2.8 0.3 89 0.16 Haycock and Burt (1993)
Herbaceous subsurface 10 NO3– 7 0.3 96 0.67 Hefting et al. (2003)
Herbaceous subsurface 100 NO3– 375 < 5 98 3.70 Prach and Rauch (1992)
Herbaceous subsurface 10 NO3– 7.54 0.05 99 0.75 Schoonover and Williard (2003)
Herbaceous subsurface 30 NO3– 44.7 0.45 99 1.48 Vidon and Hill (2004)
Herbaceous subsurface 50 NO3– 6.6 0.02 100 0.13 Martin et al. (1999)
Herbaceous/forest surface 7.5 Total N 68 49 28 – Schmitt et al. (1999)
Herbaceous/forest surface 15 Total N 68 40 41 – Schmitt et al. (1999)
Herbaceous/forest surface 16.3 NO3– – – 78 – Lee et al. (2003)
Herbaceous/forest subsurface 8 NO3– – – 69 – Dukes et al. (2002){dagger}
Herbaceous/forest subsurface 15 NO3– – – 84 – Dukes et al. (2002){dagger}
Herbaceous/forest subsurface 6 NO3– 6.17 0.56 91 0.94 Borin and Bigon (2002)
Herbaceous/forest subsurface 70 NO3– 11.98 1.09 91 0.16 Hubbard and Lowrance (1997)
Herbaceous/forest subsurface 66 NO3– 5.8 0.17 97 0.09 Vidon and Hill (2004)
Herbaceous/forest subsurface 33 NO3– 5.7 0.11 98 0.17 Vidon and Hill (2004)
Herbaceous/forest subsurface 45 NO3– 17.8 0.18 99 0.39 Vidon and Hill (2004)
Herbaceous/forest subsurface 70 NO3– 1.65 0.02 99 0.02 Martin et al. (1999)
Forest surface 30 NO3– 0.37 0.08 78 0.01 Lynch et al. (1985)
Forest surface 70 NO3– 4.45 0.94 79 0.05 Peterjohn and Correll (1984)
Forest subsurface 50 NO3– 26 11 58 0.30 Hefting et al. (2003)
Forest subsurface 200 NO3– 11 4 64 0.04 Spruill (2004)
Forest subsurface 10 NO3– 6.29 1.15 82 0.51 Schoonover and Williard (2003)
Forest subsurface 14 NO3– 0.02 0.02 0 0.00 Sabater et al. (2003)
Forest subsurface 30 NO3– 0.02 0.01 50 <0.01 Sabater et al. (2003)
Forest subsurface 50 NO3– 0.49 0.76 –55 –0.01 Sabater et al. (2003)
Forest subsurface 15 NO3– 28.64 35.84 –25 –0.48 Sabater et al. (2003)
Forest subsurface 20 NO3– 1.14 0.70 39 0.02 Sabater et al. (2003)
Forest subsurface 20 NO3– 0.12 0.43 –258 –0.02 Sabater et al. (2003)
Forest subsurface 15 NO3– 3.23 0.72 78 0.17 Sabater et al. (2003)
Forest subsurface 20 NO3– 6.40 1.44 78 0.25 Sabater et al. (2003)
Forest subsurface 55 NO3– – – 83 – Lowrance et al. (1984)
Forest subsurface 20 NO3– – – 83 – Schultz et al. (1995)
Forest subsurface 85 NO3– 7.08 0.43 94 0.08 Peterjohn and Correll (1984)
Forest subsurface 204 NO3– 29.4 1.76 94 0.14 Vidon and Hill (2004)
Forest subsurface 50 NO3– 13.52 0.81 94 0.25 Lowrance (1992)
Forest subsurface 60 NO3– 8 0.4 95 0.13 Jordan et al. (1993)
Forest subsurface 16 NO3– 16.5 0.75 95 0.98 Osborne and Kovacic (1993)
Forest subsurface 16 NO3– 6.6 0.3 95 0.39 Haycock and Pinay (1993)
Forest subsurface 15 NO3– – – 96 – Hubbard and Sheridan (1989)
Forest subsurface 165 NO3– 30.8 1 97 0.18 Hill et al. (2000)
Forest subsurface 50 NO3– 6.26 0.15 98 0.12 Hefting and de Klein (1998)
Forest subsurface 220 NO3– 10.8 0.22 98 0.05 Vidon and Hill (2004)
Forest subsurface 50 NO3– 7.45 0.1 99 0.15 Jacobs and Gilliam (1985)
Forest subsurface 10 NO3– 13 0.1 99 1.29 Cey et al. (1999)
Forest subsurface 100 NO3– 5.6 0.02 100 0.06 Spruill (2004)
Forest subsurface 30 NO3– 1.32 nd 100 0.04 Pinay and Decamps (1988)
Forest subsurface 100 NO3– 12 nd 100 0.12 Spruill (2004)
Forest subsurface 60 NO3– – – 27 – Groffman et al. (1996)
Forest subsurface 30 NO3– – – 68 – Spruill (2000){ddagger}
Forested wetland subsurface 31 NO3– 62.7 25.9 59 1.19 Hanson et al. (1994)
Forested wetland subsurface 38 NO3– 30.6 6.7 78 0.63 Vellidis et al. (2003)
Forested wetland subsurface 14.6 NO3– – – 84 – Simmons et al. (1992)
Forested wetland subsurface 5.8 NO3– – – 87 – Simmons et al. (1992)
Forested wetland subsurface 5.8 NO3– – – 90 – Simmons et al. (1992)
Forested wetland subsurface 6.6 NO3– – – 97 – Simmons et al. (1992)
Forested wetland subsurface 30 NO3– 1.06 nd 100 0.04 Pinay et al. (1993)
Wetland surface 20 NO3– 57 50 12 0.35 Brüsch and Nilsson (1993)
Wetland surface 20 NO3– 57 15 74 2.10 Brüsch and Nilsson (1993)
Wetland subsurface 5 NO3– 6.56 1.55 76 1.00 Clausen et al. (2000)
Wetland subsurface 5 NO3– 3 1.44 52 0.31 Clausen et al. (2000)
Wetland subsurface 1 NO3– 1 – 96 – Burns and Nguyen (2002)
Wetland subsurface 200 NO3– 10.5 0.5 95 0.05 Fustec et al. (1991)
Wetland
 subsurface
 40
 NO3–
 77.48
 0.31
 100
 1.93
 Puckett et al. (2002)

{dagger} Values represent the average of 16 buffers.

{ddagger} Values represent the average of 14 buffers.


   ACKNOWLEDGMENTS
 
We are grateful to S. Sabater for providing original data associated with Sabater et al. (2003). T. Wiggins assisted in the search for literature. This manuscript benefited from comments by D. Niyogi, D. Walters, S. Wenger, and three anonymous reviewers. The USEPA through its Office of Research and Development funded and managed the research described here through in-house efforts. This manuscript has not been subject to EPA review; therefore it does not necessarily reflect the views of the EPA and no official endorsement should be inferred.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 




This article has been cited by other articles:


Home page
 J. Environ. Qual.Home page
W. A. Pratt and T. R. Fox
Streamside Management Zones Effectiveness for Protecting Water Quality after Forestland Application of Biosolids
J. Environ. Qual., August 24, 2009; 38(5): 2106 - 2120.
[Abstract] [Full Text] [PDF]

Home page
 J. Environ. Qual.Home page
J. T. Walker, J. M. Vose, J. Knoepp, and C. D. Geron
Recovery of Nitrogen Pools and Processes in Degraded Riparian Zones in the Southern Appalachians
J. Environ. Qual., May 20, 2009; 38(4): 1391 - 1399.
[Abstract] [Full Text] [PDF]

Home page
 Progress in Physical GeographyHome page
Yihe Lu, Liding Chen, and Bojie Fu
Land-cover effects on red soil rehabilitation in China: a meta-analysis
Progress in Physical Geography, October 1, 2008; 32(5): 491 - 502.
[Abstract] [PDF]

Home page
 J. Environ. Qual.Home page
X. Liu, X. Zhang, and M. Zhang
Major Factors Influencing the Efficacy of Vegetated Buffers on Sediment Trapping: A Review and Analysis
J. Environ. Qual., August 8, 2008; 37(5): 1667 - 1674.
[Abstract] [Full Text] [PDF]

Home page
 Journal of Soil and Water ConservationHome page
M.G. Dosskey, M.J. Helmers, and D.E. Eisenhauer
A design aid for determining width of filter strips
Journal of Soil and Water Conservation, July 1, 2008; 63(4): 232 - 241.
[Abstract] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF) Free
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Mayer, P. M.
Right arrow Articles by Canfield, T. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Mayer, P. M.
Right arrow Articles by Canfield, T. J.
Agricola
Right arrow Articles by Mayer, P. M.
Right arrow Articles by Canfield, T. J.
Related Collections
Right arrow Ecosystem Management
Right arrow Best Management Practices
Right arrow Ground Water Quality

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
The SCI Journals Agronomy Journal Crop Science
Journal of Natural Resources
and Life Sciences Education		 Vadose Zone Journal
Soil Science Society of America Journal Journal of Plant Registrations The Plant Genome