4.4 Article

Estimating and scaling stream ecosystem metabolism along channels with heterogeneous substrate

期刊

ECOHYDROLOGY
卷 6, 期 4, 页码 679-688

出版社

WILEY
DOI: 10.1002/eco.1391

关键词

photosynthesis; respiration; gross primary production; fluid mechanics

资金

  1. National Center for Earth-surface Dynamics (NCED)
  2. Science and Technology Center
  3. Office of Integrative Activities of the National Science Foundation [EAR-0120914]
  4. Directorate For Geosciences
  5. Division Of Earth Sciences [1242458] Funding Source: National Science Foundation
  6. Directorate For Geosciences
  7. ICER [1342944] Funding Source: National Science Foundation
  8. Div Of Chem, Bioeng, Env, & Transp Sys
  9. Directorate For Engineering [1209402] Funding Source: National Science Foundation

向作者/读者索取更多资源

Measured diurnal curves of dissolved oxygen (DO) concentration have been used to estimate the gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NP) of aquatic communities. Open-system one-station and two-station methods have been employed to estimate the rate of NP, R, and GPP. We conducted field measurements in Minnehaha Creek, MN (44 degrees 56'N, 93 degrees 28'W), to quantify the spatial and temporal variabilities of DO concentrations and, consequently, evaluated the estimates of NP. Dimensionless analysis of DO mass balance revealed the dominance of local photosynthesis over respiration, advection, re-aeration, and dispersion along the studied reach. Two alternative estimation methods of stream metabolism provided similar estimates of NP with 0.65>k(a)T(a)>0.17 within the studied reach where k(a) is the re-aeration rate and T-a is the water parcel average travel time. The spatial variability of DO change along the creek revealed an average length scale of 10 m over which DO exhibited significant autocorrelation. The autotrophic-heterotrophic balance, quantified by GPP to R ratio, scaled with local stream geomorphic and hydraulic conditions from diverse geographic areas, providing useful predictive relationships expressed in terms of easily measurable abiotic parameters. Copyright (C) 2013 John Wiley & Sons, Ltd.

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