Streams play a key role in the global carbon cycle. The balance between carbon intake through photosynthesis and carbon release via respiration influences carbon emissions from streams and depends on temperature. However, the lack of a comprehensive analysis of the temperature sensitivity of the metabolic balance in inland waters across latitudes and local climate conditions hinders an accurate projection of carbon emissions in a warmer future. Here, we use a model of diel dissolved oxygen dynamics, combined with high-frequency measurements of dissolved oxygen, light and temperature, to estimate the temperature sensitivities of gross primary production and ecosystem respiration in streams across six biomes, from the tropics to the arctic tundra. We find that the change in metabolic balance, that is, the ratio of gross primary production to ecosystem respiration, is a function of stream temperature and current metabolic balance. Applying this relationship to the global compilation of stream metabolism data, we find that a 1 °C increase in stream temperature leads to a convergence of metabolic balance and to a 23.6% overall decline in net ecosystem productivity across the streams studied. We suggest that if the relationship holds for similarly sized streams around the globe, the warming-induced shifts in metabolic balance will result in an increase of 0.0194 Pg carbon emitted from such streams every year.

%B Nature Geoscience %V 11 %P 415 - 420 %G eng %U http://www.nature.com/articles/s41561-018-0125-5 %N 6 %M KNZ001918 %R 10.1038/s41561-018-0125-5 %0 Journal Article %J Freshwater Biology %D 2017 %T Probing whole-stream metabolism: influence of spatial heterogeneity on rate estimates %A Siders, Adam C. %A Larson, Danelle M. %A Rüegg, Janine %A W. K. Dodds %X1. Whole-stream metabolism has been estimated by measuring in-stream oxygen (O2) concentrations since the method was introduced over 50 years ago. However, the influence of measurement location and estimation method on metabolism rates is understudied. We examined how the placement of O2 probes (i.e. depth, separation from the thalweg), differences in methodology (1-station, 2-station, area-weighted) and reach lengths influenced estimated rates of whole-stream metabolism in a tallgrass prairie watershed.

2. Metabolism estimates made in the thalweg differed from estimates made in backwaters due to disconnection in flow, and estimates made in deep pools differed from surface estimates due to thermal stratification (temporary flow disconnection). The 1-station respiration estimates differed from short 2-station reach-scale estimates (c. 20 m) but were more similar to larger 2-station reach-scale estimates (c. 100 m). In contrast, the 1-station gross primary production was most similar to the short 2-station reaches occurring immediately upstream and became less similar at longer 2-station reach lengths. The different estimation methodologies (1-station, 2-station, area-weighted) accounting for the longest reach scale did not result in different metabolism rates.

3. The temporary phenomena of thermal stratification of stream pools during a warm day, which disconnected pool bottoms from the surface waters, likely affected not only the pool estimates but also estimates made in the downstream thalweg (i.e. an O2 deficit accrued from respiration during the day in the bottom of the pool abruptly moved downstream during mixing).

4. Oxygen probe placement mattered and affected rate estimates according to habitat type and reach length (i.e. scale) due to the influence of small-scale heterogeneity on community respiration. Selection of reach length can be critical for studies depending on whether local heterogeneity is of interest or should be averaged.

5. We conclude that the intuitive use of thalwegs and reaches that are at least 10 times the stream width are likely appropriate for whole-stream metabolism estimates, although the exact reach length necessary and potential stream-specific characteristics, such as stratified pools, need to be carefully considered in probe placement. We encourage other studies to report the placement characteristics of O2 probes in streams as well as consider the potential confounding factor of local habitat heterogeneity.

%B Freshwater Biology %V 62 %P 711 - 723 %G eng %U https://onlinelibrary.wiley.com/doi/abs/10.1111/fwb.12896 %N 4 %M KNZ001831 %R 10.1111/fwb.12896 %0 Journal Article %J Landscape Ecology %D 2016 %T Baseflow physical characteristics differ at multiple spatial scales in stream networks across diverse biomes %A Rüegg, Janine %A W. K. Dodds %A Daniels, M.D. %A Sheehan, Ken R. %A Baker, Christina L. %A W.B. Bowden %A Farrell, Kaitlin J. %A Flinn, Michael B. %A Harms, Tamara K. %A Jones, J.B. %A Koenig, Lauren E. %A Kominoski, John S. %A W.H. McDowell %A Parker, Samuel P. %A Rosemond, Amy D. %A Trentman, Matt T. %A M.R. Whiles %A Wollheim, Wilfred M. %K Boreal forest %K Geomorphology %K Grasslands %K Nested ANOVA %K Scaling %K Temperate forest %XContext Spatial scaling of ecological processes is facilitated by quantifying underlying habitat attributes. Physical and ecological patterns are often measured at disparate spatial scales limiting our ability to quantify ecological processes at broader spatial scales using physical attributes. Objective We characterized variation of physical stream attributes during periods of high biological activity (i.e., baseflow) to match physical and ecological measurements and to identify the spatial scales exhibiting and predicting heterogeneity. Methods We measured canopy cover, wetted width, water depth, and sediment size along transects of 1st–5th order reaches in five stream networks located in biomes from tropical forest to arctic tundra. We used hierarchical analysis of variance with three nested scales (watersheds, stream orders, reaches) to identify scales exhibiting significant heterogeneity in attributes and regression analyses to characterize gradients within and across stream networks. Results Heterogeneity was evident at one or multiple spatial scales: canopy cover and water depth varied significantly at all three spatial scales while wetted width varied at two scales (stream order and reach) and sediment size remained largely unexplained. Similarly, prediction by drainage area depended on the attribute considered: depending on the watershed, increases in wetted width and water depth with drainage area were best fit with a linear, logarithmic, or power function. Variation in sediment size was independent of drainage area. Conclusions The scaling of ecologically relevant baseflow physical characteristics will require study beyond the traditional bankfull geomorphology since predictions of baseflow physical attributes by drainage area were not always best explained by geomorphic power laws.

%B Landscape Ecology %V 31 %P 119-136 %G eng %U https://link.springer.com/article/10.1007%2Fs10980-015-0289-y %N 1 %M KNZ001708 %R 10.1007/s10980-015-0289-y %0 Journal Article %J Limnology and Oceanography: Methods %D 2016 %T Methods of approximation influence aquatic ecosystem metabolism estimates %A Song, Chao %A W. K. Dodds %A Trentman, Matt T. %A Rüegg, Janine %A Ballantyne, Ford %XAquatic ecologists have recently employed dynamic models to estimate aquatic ecosystem metabolism. All approaches involve numerically solving a differential equation describing dissolved oxygen (DO) dynamics. Although the DO differential equation can be solved accurately with linear multistep or Runge–Kutta methods, less accurate methods, such as the Euler method, have been applied. The methods also differ in how discrete temperature and light measurements are used to drive DO dynamics. Here, we used a representative stream DO data set to compare the metabolism estimates generated by multiple Euler based methods and an accurate numerical method. We also compared metabolism estimates using linear, piecewise constant and smoothing spline interpolation of light and temperature. Using observed DO to calculate DO saturation deficit in the Euler method results in a substantial difference in metabolism estimates compared to all other methods. If modeled DO is used to calculate DO saturation deficit, the Euler method introduces smaller error in metabolism estimates, which diminishes as logging interval decreases. Linear and smoothing spline interpolation result in similar metabolism estimates, but differ from estimates based on piecewise constant interpolation. We demonstrate how different computational methods imply distinct assumptions about process and observation error, and conclude that under the assumption of observation error, the best practice is to use the accurate numerical method of solving differential equation with a continuous interpolation of light and temperature. The Euler method will introduce minimal error if it is paired with frequently logged data and DO saturation deficit is computed using modeled DO.

%B Limnology and Oceanography: Methods %V 14 %P 557 - 569 %G eng %U https://aslopubs.onlinelibrary.wiley.com/doi/full/10.1002/lom3.10112 %N 9 %M KNZ001867 %R 10.1002/lom3.10112