Channel complexity and nitrate concentrations drive denitrification rates in urban restored and unrestored streams

Tuttle, A. K.; McMillan, Sara K.; Gardner, Angela; Jennings, Gregory D.

doi:10.1016/j.ecoleng.2014.09.066

Cited by 23 publications

(15 citation statements)

References 49 publications

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“…Stream channel complexity has been defined in many ways [ Palmer et al ., ], but generally refers to heterogeneity of physical stream geometry or habitat. We distinguish geomorphic complexity, which is spatial heterogeneity of channel substrate, bed forms, cross‐sectional geometry, planform, and downstream gradient [e.g., Gooseff et al ., ; Bertoldi et al ., ; Legleiter , ; Tuttle et al ., ], from habitat complexity, which relates to niche diversity [ Peipoch et al ., ]. Geomorphic complexity does not necessarily correlate to habitat complexity.…”

Section: Introductionmentioning

confidence: 99%

Sources and interpretation of channel complexity in forested subalpine streams of the Southern Rocky Mountains

Livers

Wohl

2016

Water Resources Research

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We evaluate correlations between stream geomorphic complexity and characteristics of the adjacent riparian forest, valley geometry, and land use history in forested subalpine streams of the Colorado Front Range. Measures of geomorphic complexity focus on cross-sectional, planform, and instream wood piece and logjam variables. We categorize adjacent riparian forests as old-growth unmanaged forest (OU), younger unmanaged forest (YU), and younger managed forest (YM), and valley geometry as laterally confined, partly confined, or unconfined. Significant differences in geomorphic stream complexity between OU, YU, and YM result primarily from differences in wood pieces and logjams, and these differences correlate strongly with pool volume and organic matter storage. Significant differences in planform and crosssectional complexity correlate more strongly with valley geometry, but do not explain as much of the observed variability in complexity between streams as do the wood variables. Unconfined OU streams have the largest wood loads and the greatest complexity, whereas legacy effects of logging, tie-drives, and channel simplification create lower complexity in YM streams, even relative to YU streams flowing through similarly aged forest. We find that management history of riparian forests exerts the strongest control on reduced functional stream channel complexity, regardless of riparian forest stand age. PUBLICATIONSbut this relationship has been difficult to demonstrate in the field [Palmer et al., 2010]. Although previous studies have related geomorphic complexity of floodplain and instream units to riparian plant species in natural watersheds [Harris, 1988] and watersheds disturbed by human activity [Hupp and Rinaldi, 2007;Gumiero et al., 2015], they do not evaluate such complexity in relation to variations in valley geometry and forest disturbance history. In this paper, we evaluate correlations between different measures of geomorphic complexity in small mountain streams of the Colorado Front Range and characteristics of the adjacent riparian forest, valley geometry, and land use history.Exchanges of water, sediment, and organic matter within and between terrestrial and stream environments influence physical and biological stream dynamics, as well as ecological food webs [Baxter et al., 2005], in turn influencing geomorphic complexity. In this context, riparian forest stand age can exert a particularly important indirect influence on channel complexity by serving as a control on the recruitment of large wood (10 cm diameter and 1 m length) to channels. Trees in old-growth forests (200 years stand age) are larger in diameter and thus greater in volume than trees in younger growth forests. Trees with greater diameter are less likely to be transported downstream in small streams due to the relative dimensions of wood pieces and channels [Braudrick et al.are thus retained close to where they fall in the stream [Lienkaemper and Swanson, 1986;Wohl and Jaeger, 2009] and have greater potential to trap mobile wood and fo...

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Section: Introductionmentioning

confidence: 99%

Sources and interpretation of channel complexity in forested subalpine streams of the Southern Rocky Mountains

Livers

Wohl

2016

Water Resources Research

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“…Previous modeling studies have demonstrated that SCMs can increase geomorphic stability and reduce stream erosion potential, particularly for coarse stream bed material [21,60]. While we did not directly measure changes in bed material or erosion rates, we observed increases in denitrification downstream of areas with increased channel residence time (e.g., beaver ponds), which suggests that slower velocities may also enhance depositional processes, particularly of finer sediments that have been shown to have higher rates of denitrification and metabolism [15,16,61]. We also observed elevated rates along the stream reach and hypothesize that these may be influenced by inputs of additional SCMs along the stream reach (e.g., SP), and/or increased water residence times within the channel because of backwater effects and/or beaver wetland creation (e.g., SL and UP, respectively).…”

Section: Influence Of Scm Inputs On Instream Denitrificationmentioning

confidence: 82%

“…Controls on denitrification followed patterns well-established in many other natural and human-influenced streams including resource availability and hydrologic conditions [16,17,48,61]. By using two complementary methods to quantify denitrification rates, we were able to assess the drivers of variability across a range of environmental conditions.…”

Section: Environmental Controlsmentioning

confidence: 99%

Effects of Urban Stormwater Control Measures on Denitrification in Receiving Streams

Rivers

McMillan

Bell

et al. 2018

Water

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Urban areas are increasingly adopting the use of ecologically-based technologies for stormwater management to mitigate the effects of impervious surface runoff on receiving water bodies. While stormwater control measures (SCMs) reduce runoff, their ability to influence ecosystem function in receiving streams is not well known. To understand the effect of SCMs on net ecosystem function in stream networks, we measured sediment denitrification in four streams across a gradient of urban and suburban residential development in Charlotte, NC. We evaluated the influence of SCM inputs on actual (DNF) and potential (DEA) denitrification activity in stream sediments at the SCM-stream confluence to quantify microbial processes and the environmental factors that control them. DNF was variable across sites, ranging from 0–6.60 mg-N·m−2·h−1 and highly correlated with in-stream nitrate (NO3-N) concentrations. Sites with a greater impervious area showed a pattern of significantly higher DEA rates upstream of the SCM compared to downstream, while sites with less imperviousness showed the opposite trend. We hypothesize that this is because of elevated concentrations of carbon and nitrogen provided by pond and wetland outflows, and stabilization of the benthic habitat by lower peak discharge. These results suggest that SCMs integrated into the watershed have the potential to create cascading positive effects on in-stream nutrient processing and thereby improve water quality; however, at higher levels of imperviousness, the capacity for SCMs to match the scale of the impacts of urbanization likely diminishes.

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“…A number of biogeochemical factors such as sunlight exposure, nutrient concentrations (O'Brien, Dodds, Wilson, Murdock, & Eichmiller, ; von Schiller et al, ), availability of organic matter, and contact with benthic communities (Arango, Tank, Johnson, & Hamilton, ; Craig et al, ) have been found to explain variability of in‐stream nutrient fluxes. In addition, morphological aspects including connectivity with stream banks (Heffernan et al, ; Kaushal, Groffman, Mayer, Striz, & Gold, ; Mayer, Schechter, Kaushal, & Groffman, ) and channel complexity (Bernhardt, Band, Walsh, & Berke, ; McMillen, Jennings, Gardner, & Tuttle, ; Tuttle, McMillan, Gardner, & Jennings, ) are also known to affect nutrient fluxes. All of these factors vary temporally (across years, seasons, and storm events) and spatially (interstream and intrastream).…”

Section: Introductionmentioning

confidence: 99%

“…Despite being the prevalent regime in some streams during the wet season outside runoff events (Petrone, ), nutrient retention during high base flows has been poorly studied. This hydrological regime is expected to decrease nutrient retention around natural or artificial in‐stream features such as deep pools, cross vanes, log weirs, riffles, gravel bars, and debris dams (Arango, James, & Hatch, ; Claessens, Tague, Groffman, & Melack, ; Hines & Hershey, ; Kaushal et al, ; Tuttle et al, ) due to the low contact time (Bukaveckas, ). In addition, although these features are known to improve habitat, reduce flow velocities, promote carbon accumulation, enhance transient storage, and promote hyporheic exchange (Craig et al, ; Crispell & Endreny, ; Gift, Groffman, Kaushal, & Mayer, ), the high discharge velocity characteristic of this regime can cause displacement and damage to these retentive features and further impair nutrient retention (Groffman, Dorsey, & Mayer, ; Walsh et al, ).…”

Section: Introductionmentioning

confidence: 99%

Spatial and temporal characterization of nutrient net uptake in a vegetated urban stream: Stream bank features leading to net uptake hotspots

Singh

Oldham

2017

Hydrological Processes

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Urban stream features can be used to promote nutrient retention; however, their interactions with different hydrological regimes impact nutrient cycling, decrease their retention capacity, and inhibit stream ecosystem functioning. This study analysed the temporal and spatial dynamics of the uptake of three nutrients (nitrate, ammonium, and phosphorus) in an urban drainage stream during high flows. In particular, we studied variations in net uptake along the right margin (with native vegetation and a roots mat) comparatively to the left margin (a non-rooted grassy bank).Applying the spiralling approach within each subreach on either side, we determined nutrient subreach (sr) retention metrics: uptake rate coefficients K sr net , mass transfer rates vf sr net À Á , and areal uptake rates U sr net À Á . Our results showed nitrate (NO 3 ) and ammonium (NH 4 ) net uptakes on the right side were higher and more frequent along subreaches where the root mat was more abundant (U sr net [μg m −2 s −1 ] = 22.80 ± 1.13 for NO 3 and 10.50 ± 0.81 for NH 4 ), whereas on the left side both nutrients showed patchy and inconsistent net uptake patterns despite the homogeneous grass distribution. Net uptake for filtered reactive phosphorus (FRP) was not observed on either side at any flow rate. The impact of hydrological factors such as discharge, travel time, water depth, and concentration, on uptake metrics was studied. Despite increases in travel time as the flow decreased, there was a reduction in net uptake rates, vf sr net and U sr net , on either side. This was attributed to a reduction in water level with declining flows, which decreased hydrologic connectivity with the stream banks, combined with a decrease in water velocity and a reduction in nutrient concentrations. We concluded the rooted bank acted as an effective retention area by systematically promoting net uptake resulting in a twofold increased dissolved inorganic nitrogen (DIN) retention relative to the non-rooted side where net uptake was spatially localized and highly dynamic.Overall, this work emphasized the importance of strategically sampling close to biologically active surfaces to more accurately determine areas where gross uptake surpasses release process.

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Channel complexity and nitrate concentrations drive denitrification rates in urban restored and unrestored streams

Cited by 23 publications

References 49 publications

Sources and interpretation of channel complexity in forested subalpine streams of the Southern Rocky Mountains

Sources and interpretation of channel complexity in forested subalpine streams of the Southern Rocky Mountains

Effects of Urban Stormwater Control Measures on Denitrification in Receiving Streams

Spatial and temporal characterization of nutrient net uptake in a vegetated urban stream: Stream bank features leading to net uptake hotspots

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