00605nas a2200169 4500008004100000245012600041210006900167300001400236490000700250100002400257700001600281700002000297700001900317700002300336700001800359856005800377 2022 eng d00aPrairie stream metabolism recovery varies based on antecedent hydrology across a stream network after a bank‐full flood0 aPrairie stream metabolism recovery varies based on antecedent hy a1986-19990 v671 aRuffing, Claire, M.1 aVeach, A.M.1 aSchechner, Anne1 aRüegg, Janine1 aTrentman, Matt, T.1 aDodds, W., K. uhttps://onlinelibrary.wiley.com/doi/10.1002/lno.1218202718nas 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

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.

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/s41561-018-0125-502298nas a2200121 4500008004100000245015800041210006900199300001200268490000700280520181100287100002302098856005502121 2018 eng d00aThe impact of long-term regional air mass patterns on nutrient precipitation chemistry and nutrient deposition within a United States grassland ecosystem0 aimpact of longterm regional air mass patterns on nutrient precip a399-4100 v753 a

Changes in the frequency of precipitation as a result of a changing climate, as well as anthropogenic induced deposition of nitrogen (N), both have the potential to alter grassland productivity and diversity. Central U.S. weather patterns are dominated by three major air mass trajectories including regional sources from the Gulf of Mexico (marine tropical, Mt), the Pacific Northwest (mild pacific, mP), and the Desert Southwest (continental tropical, Ct). In this work, the Hybrid Single Particle Lagrangian Integrated Trajectory model was used to determine trends in the proportion of precipitation events from these air mass sources from 1983 to 2006 relative to Konza Prairie Biological Station (KPBS), KS. The annual volume-weighted mean (VWM) concentrations and wet deposition of a variety of precipitation dissolved solutes were linked to source regions north or south of KPBS. The proportion of precipitation events from Mt significantly increased, while the proportion of events from Ct and mP decreased significantly over the study period. The annual VWM concentrations of most solutes were typically higher from precipitation sourced to the north of KPBS. However, wet deposition of four ecologically relevant solutes (NH4+, NO3, H+, and SO4−2) was higher from events from the southern region, likely due to higher precipitation amounts. The proportion of reduced N increased significantly over the study period but was not affected by source region despite the higher use of fertilizers for agriculture in the northern source region. Given the location of this site relative to three dominant air mass paths, future shifts in these patterns will likely impact wet nutrient deposition.

1 aTrentman, Matt, T. uhttp://link.springer.com/10.1007/s10874-018-9384-103056nas a2200409 4500008004100000022001400041245011300055210006900168300001200237490000700249520184200256653001802098653001802116653001502134653001702149653001202166653002102178100001902199700001802218700001802236700002102254700002502275700001702300700002502317700002302342700002202365700001602387700002302403700002402426700001902450700002302469700002202492700002302514700001702537700002602554856006602580 2016 eng d a0921-297300aBaseflow physical characteristics differ at multiple spatial scales in stream networks across diverse biomes0 aBaseflow physical characteristics differ at multiple spatial sca a119-1360 v313 a

Context 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.

10aBoreal forest10aGeomorphology10aGrasslands10aNested ANOVA10aScaling10aTemperate forest1 aRüegg, Janine1 aDodds, W., K.1 aDaniels, M.D.1 aSheehan, Ken, R.1 aBaker, Christina, L.1 aBowden, W.B.1 aFarrell, Kaitlin, J.1 aFlinn, Michael, B.1 aHarms, Tamara, K.1 aJones, J.B.1 aKoenig, Lauren, E.1 aKominoski, John, S.1 aMcDowell, W.H.1 aParker, Samuel, P.1 aRosemond, Amy, D.1 aTrentman, Matt, T.1 aWhiles, M.R.1 aWollheim, Wilfred, M. uhttps://link.springer.com/article/10.1007%2Fs10980-015-0289-y02310nas a2200169 4500008004100000245007800041210006900119300001400188490000700202520176200209100001501971700001801986700002302004700001902027700002102046856007302067 2016 eng d00aMethods of approximation influence aquatic ecosystem metabolism estimates0 aMethods of approximation influence aquatic ecosystem metabolism  a557 - 5690 v143 a

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–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.

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