Basin-scale availability of salmonid spawning gravel as influenced by channel type and hydraulic roughness in mountain catchments

Buffington, John M.; Montgomery, David R.; Greenberg, Harvey

doi:10.1139/f04-141

Cited by 125 publications

(185 citation statements)

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“…Our scaling laws allow one to quantify N 2 O emissions at the watershed scale using geographic information system analyses of stream morphology (44) and readily available measurements of nitrate and ammonium, which can be distributed throughout the river network, both in space and through time (45). This approach requires robust hyporheic models linked to hydromorphological information.…”

Section: Resultsmentioning

confidence: 99%

Role of surface and subsurface processes in scaling N ₂ O emissions along riverine networks

Marzadri

Dee

Tonina

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

118

147

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Riverine environments, such as streams and rivers, have been reported as sources of the potent greenhouse gas nitrous oxide (N 2 O) to the atmosphere mainly via microbially mediated denitrification. Our limited understanding of the relative roles of the nearsurface streambed sediment (hyporheic zone), benthic, and water column zones in controlling N 2 O production precludes predictions of N 2 O emissions along riverine networks. Here, we analyze N 2 O emissions from streams and rivers worldwide of different sizes, morphology, land cover, biomes, and climatic conditions. We show that the primary source of N 2 O emissions varies with stream and river size and shifts from the hyporheic-benthic zone in headwater streams to the benthic-water column zone in rivers. This analysis reveals that N 2 O production is bounded between two N 2 O emission potentials: the upper N 2 O emission potential results from production within the benthic-hyporheic zone, and the lower N 2 O emission potential reflects the production within the benthic-water column zone. By understanding the scaling nature of N 2 O production along riverine networks, our framework facilitates predictions of riverine N 2 O emissions globally using widely accessible chemical and hydromorphological datasets and thus, quantifies the effect of human activity and natural processes on N 2 O production.riverine networks | greenhouse gas | N 2 O | emission scaling law | N 2 O emission potentials R iverine environments, such as streams and rivers, have been identified as hotspots of microbially mediated denitrification, where nitrate (NO3) is converted to both nitrogen gas (N2), which constitutes the majority of Earth's atmosphere, and nitrous oxide (N 2 O), the potent greenhouse gas responsible for stratospheric ozone destruction (1). Denitrification has been observed to occur within both bulk-oxic (2) and anoxic environments (3-5) of both benthic (i.e., sediment-water interface) and hyporheic (i.e., near-subsurface) zones of streams and rivers. Whereas the benthic zone is the ecological region of the streambed, where both aquatic fauna and flora can be found (4, 6), the latter is the band of streambed material mainly saturated of stream water (7). The benthic zone is at the interface between water and sediment and the upper boundary of the fluvial hyporheic zone. Current understanding suggests that riverine N 2 O production occurs predominantly in these two environments, reflecting two distinct biogeochemical transformation zones (6), irrespective of system size from headwater streams to rivers. The produced N 2 O is then exchanged with the atmosphere through diffusive evasion, with dynamics that depend on N 2 O concentrations of the water in relation to atmospheric equilibrium (6, 8), stream hydrodynamics, temperature, and the air-water gas exchange rate (9). Although it is understood that microbially mediated denitrification is responsible for a large proportion of N 2 O production in riverine networks (6, 10, 11), quantifying these emissions is challenging becau...

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Section: Resultsmentioning

confidence: 99%

Role of surface and subsurface processes in scaling N ₂ O emissions along riverine networks

Marzadri

Dee

Tonina

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

118

147

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“…We estimated bankfull channel width, depth, and mean annual flow using regional regressions (Kresch, 1998;Magirl and Olsen, 2009) to predict spatially averaged conditions, but acknowledge the great spatial variability in hydraulic geometry driven by complexities (floodplains, log jams, boulders) that we did not model; a similar approach has been used by others (Beechie and Imaki, 2014;Clarke et al, 2008). We used the watershed analysis software, NetMap www.terrainworks.com), to predict channel type (cascade, step-pool, pool-riffle, plane-bed) and substrate D50 (using a regional regression appropriate for the Pacific Northwest from Buffington et al, 2004). The spatial extent of our modeling went beyond the current and historic distribution of spring Chinook.…”

Section: Predicting Physical Effects Of Fire On Stream Channelsmentioning

confidence: 99%

Wildfire may increase habitat quality for spring Chinook salmon in the Wenatchee River subbasin, WA, USA

Flitcroft

Falke

Reeves

et al. 2016

Forest Ecology and Management

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a b s t r a c tPacific Northwest salmonids are adapted to natural disturbance regimes that create dynamic habitat patterns over space and through time. However, human land use, particularly long-term fire suppression, has altered the intensity and frequency of wildfire in forested upland and riparian areas. To examine the potential impacts of wildfire on aquatic systems, we developed stream-reach-scale models of freshwater habitat for three life stages (adult, egg/fry, and juvenile) of spring Chinook salmon (Oncorhynchus tshawytscha) in the Wenatchee River subbasin, Washington. We used variables representing pre-and post-fire habitat conditions and employed novel techniques to capture changes in in-stream fine sediment, wood, and water temperature. Watershed-scale comparisons of high-quality habitat for each life stage of spring Chinook salmon habitat suggested that there are smaller quantities of high-quality juvenile overwinter habitat as compared to habitat for other life stages. We found that wildfire has the potential to increase quality of adult and overwintering juvenile habitat through increased delivery of wood, while decreasing the quality of egg and fry habitat due to the introduction of fine sediments. Model results showed the largest effect of fire on habitat quality associated with the juvenile life stage, resulting in increases in high-quality habitat in all watersheds. Due to the limited availability of pre-fire high-quality juvenile habitat, and increased habitat quality for this life stage post-fire, occurrence of characteristic wildfires would likely create a positive effect on spring Chinook salmon habitat in the Wenatchee River subbasin. We also compared pre-and post-fire model results of freshwater habitat for each life stage, and for the geometric mean of habitat quality across all life stages, using current compared to the historic distribution of spring Chinook salmon. We found that spring Chinook salmon are currently distributed in stream channels in which in-stream habitat for most life stages has a consistently positive response to fire. This compares to the historic distribution of spring Chinook, in which in-stream habitat exhibited a variable response to fire, including decreases in habitat quality overall or for specific life stages. This suggests that as the distribution of spring Chinook has decreased, they now occupy those areas with the most positive potential response to fire. Our work shows the potentially positive link between wildfire and aquatic habitat that supports forest managers in setting broader goals for fire management, perhaps leading to less fire suppression in some situations.Ó 2015 Published by Elsevier B.V.

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“…Predictions of potential substrate based on our understanding of the geomorphic controls of sediment size may allow us to avoid use of direct measures of substrate composition in many models. Buffington et al (2004) were able to make predictions of sediment size based on DEM-derived channel slopes and catchment area/depth relationships. Refining these models to include other controls on substrate, such as valley width (R. Hill, Utah State University, unpublished data), should further improve our predictions of substrate, and hence biota.…”

Section: Utility Of Map/gis Variables In Rivpacs Modelsmentioning

confidence: 99%

Development of a RIVPACS-type predictive model for bioassessment of wadeable streams in Wyoming

Hargett

ZumBerge

Hawkins

et al. 2007

Ecological Indicators

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RIVPACS models produce a community-level measure of biological condition known as O/E, which is derived from a comparison of the observed (O) biota with those expected (E) to occur in the absence of anthropogenic stress. We used benthic macroinvertebrate and environmental data collected at 925 stream monitoring stations, from 1993 to 2001, to develop, validate, and apply a RIVPACS model to assess the biological condition of wadeable streams in Wyoming. From this dataset, 296 samples were identified as reference, 157 of which were used to calibrate the model, 46 to validate it, and 93 to examine temporal variability in reference site O/E-values. We used cluster analyses to group the model development reference sites into biologically similar classes of streams and multiple discriminant function analysis to determine which environmental variables best discriminated among reference groups. A suite of 14 categorical and continuous environmental variables best discriminated among 15 reference groups and explained a large proportion of the natural variability in biota within the reference dataset. Eleven of the predictor variables were derived from GIS. As expected, mean O/E-values for reference sites used in model development and validation were near unity and statistically similar. Temporal variability in O/E-values for reference sites was low. Test site values ranged from 0 to 1.45 (mean = 0.73). The model was accurate in both space and time and precise enough (S.D. of O/E-values for calibration data = 0.17) to detect modest alteration in biota associated with anthropogenic stressors. Our model was comparable in performance to other RIVPACS models developed in the United States and can produce effective assessments of biological condition over a broad, ecologically diverse region. We also provide convincing evidence that RIVPACS models can be developed primarily with GISbased predictor variables. This framework not only simplifies the extraction of predictor variable information while potentially reducing expenditures of time and money in the collection of predictor variable information, but opens the door for development and/or application of RIVPACS models in regions where there is a paucity of local-scale, abiotic information. #

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Basin-scale availability of salmonid spawning gravel as influenced by channel type and hydraulic roughness in mountain catchments

Cited by 125 publications

References 42 publications

Role of surface and subsurface processes in scaling N ₂ O emissions along riverine networks

Role of surface and subsurface processes in scaling N ₂ O emissions along riverine networks

Wildfire may increase habitat quality for spring Chinook salmon in the Wenatchee River subbasin, WA, USA

Development of a RIVPACS-type predictive model for bioassessment of wadeable streams in Wyoming

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Basin-scale availability of salmonid spawning gravel as influenced by channel type and hydraulic roughness in mountain catchments

Cited by 125 publications

References 42 publications

Role of surface and subsurface processes in scaling N 2 O emissions along riverine networks

Role of surface and subsurface processes in scaling N 2 O emissions along riverine networks

Wildfire may increase habitat quality for spring Chinook salmon in the Wenatchee River subbasin, WA, USA

Development of a RIVPACS-type predictive model for bioassessment of wadeable streams in Wyoming

Contact Info

Product

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Role of surface and subsurface processes in scaling N ₂ O emissions along riverine networks

Role of surface and subsurface processes in scaling N ₂ O emissions along riverine networks