@article {KNZ002060,
	title = {SoDaH: the SOils DAta Harmonization database, an open-source synthesis of soil data from research networks, version 1.0},
	journal = {Earth System Science Data},
	volume = {13},
	year = {2021},
	pages = {1843 - 1854},
	keywords = {LTER-KNZ},
	doi = {10.5194/essd-13-1843-2021},
	url = {https://essd.copernicus.org/articles/13/1843/2021/essd-13-1843-2021.pdf},
	author = {Wieder, William R. and Pierson, Derek and Earl, Stevan and Lajtha, Kate and S.G. Baer and Ballantyne, Ford and Berhe, Asmeret Asefaw and Billings, Sharon A. and Brigham, Laurel M. and Chacon, Stephany S. and Fraterrigo, Jennifer and Frey, Serita D. and Georgiou, Katerina and de Graaff, Marie-Anne and Grandy, A. Stuart and Hartman, Melannie D. and Hobbie, Sarah E. and Johnson, Chris and Kaye, Jason and Kyker-Snowman, Emily and Litvak, Marcy E. and Mack, Michelle C. and Malhotra, Avni and Moore, Jessica A. M. and Nadelhoffer, Knute and Rasmussen, Craig and Silver, Whendee L. and Sulman, Benjamin N. and Walker, Xanthe and Weintraub, Samantha}
}
@article {KNZ001918,
	title = {Continental-scale decrease in net primary productivity in streams due to climate warming},
	journal = {Nature Geoscience},
	volume = {11},
	year = {2018},
	pages = {415 - 420},
	abstract = {<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>},
	keywords = {LTER-KNZ},
	doi = {10.1038/s41561-018-0125-5},
	url = {http://www.nature.com/articles/s41561-018-0125-5},
	author = {Song, Chao and W. K. Dodds and R{\"u}egg, Janine and Argerich, Alba and Baker, Christina L. and W.B. Bowden and Douglas, Michael M. and Farrell, Kaitlin J. and Flinn, Michael B. and Garcia, Erica A. and Helton, Ashley M. and Harms, Tamara K. and Jia, Shufang and Jones, Jeremy B. and Koenig, Lauren E. and Kominoski, John S. and McDowell, William H. and McMaster, Damien and Parker, Samuel P. and Rosemond, Amy D. and Ruffing, Claire M. and Sheehan, Ken R. and Trentman, Matt T. and M.R. Whiles and Wollheim, Wilfred M. and Ballantyne, Ford}
}
@article {KNZ001867,
	title = {Methods of approximation influence aquatic ecosystem metabolism estimates},
	journal = {Limnology and Oceanography: Methods},
	volume = {14},
	year = {2016},
	pages = {557 - 569},
	abstract = {<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>},
	keywords = {LTER-KNZ},
	doi = {10.1002/lom3.10112},
	url = {https://aslopubs.onlinelibrary.wiley.com/doi/full/10.1002/lom3.10112},
	author = {Song, Chao and W. K. Dodds and Trentman, Matt T. and R{\"u}egg, Janine and Ballantyne, Ford}
}
