02718nas a2200421   4500008004100000245009300041210006900134300001400203490000700217520145600224100001501680700001801695700001901713700001901732700002501751700001701776700002501793700002501818700002301843700002201866700002301888700002201911700001701933700002201950700002301972700002401995700002602019700002102045700002302066700002202089700002402111700002102135700002302156700001702179700002602196700002102222856005302243       2018                        eng d00aContinental-scale decrease in net primary productivity in streams due to climate warming0 aContinentalscale decrease in net primary productivity in streams  a415 - 4200 v113 a<p>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&thinsp;&deg;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&thinsp;Pg carbon emitted from such streams every year.</p>1 aSong, Chao1 aDodds, W., K.1 aRüegg, Janine1 aArgerich, Alba1 aBaker, Christina, L.1 aBowden, W.B.1 aDouglas, Michael, M.1 aFarrell, Kaitlin, J.1 aFlinn, Michael, B.1 aGarcia, Erica, A.1 aHelton, Ashley, M.1 aHarms, Tamara, K.1 aJia, Shufang1 aJones, Jeremy, B.1 aKoenig, Lauren, E.1 aKominoski, John, S.1 aMcDowell, William, H.1 aMcMaster, Damien1 aParker, Samuel, P.1 aRosemond, Amy, D.1 aRuffing, Claire, M.1 aSheehan, Ken, R.1 aTrentman, Matt, T.1 aWhiles, M.R.1 aWollheim, Wilfred, M.1 aBallantyne, Ford  uhttp://www.nature.com/articles/s41561-018-0125-502310nas a2200169   4500008004100000245007800041210006900119300001400188490000700202520176200209100001501971700001801986700002302004700001902027700002102046856007302067       2016                        eng d00aMethods of approximation influence aquatic ecosystem metabolism estimates0 aMethods of approximation influence aquatic ecosystem metabolism   a557 - 5690 v143 a<p>Aquatic 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&ndash;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.</p>1 aSong, Chao1 aDodds, W., K.1 aTrentman, Matt, T.1 aRüegg, Janine1 aBallantyne, Ford  uhttps://aslopubs.onlinelibrary.wiley.com/doi/full/10.1002/lom3.10112