# Presentation: 201173

## SOIL RESPIRATION STUDIES

- AT THE NIWOT RIDGE
- AMERIFLUX SITE

- L.E. Scott-Denton and R.K. Monson
- University of Colorado at Boulder

-   SEASONAL CONTROLS
- _Goal_: to clarify how soil moisture and soil temperature control soil respiration rates.
- We monitored soil respiration rates, soil temperature, and soil moisture at permanently established transects over three summers (Fig. 1).  Soil temperature and julian date were both found to be important to explain summer trends is soil respiration rate, whereas soil moisture was not a significant predictor (Table 1).  However differences in soil moisture between years seemed to limit summer respiration maximums.  The effects of moisture are likely obscured by the timing of the two major moisture inputs: both at the beginning of the season (snowmelt) when soil temperatures are quite low, and mid-summer (convective thunderstorms) when soil temperatures are at their maximum (Fig. 2).
- _Conclusions_: Soil moisture cannot be used to predict respiration rates perhaps due to its confounding timing with soil temperature.  However, as drought years were found to have depressed  respiration rates, moisture is an important interannual predictor of respiration.

- 2.  SPATIAL CONTROLS
- _Goal_: to identify soil variables that correlate to soil respiration rate.
- During the summer of 2000 we measured soil respiration rates on previously-imbedded collars then excavated soil cores from directly under the collars.  We measured a series of variables on the soil collars (Table 2) and used multiple-regression and multivariate statistical means to identify which variables predicted respiration rate.  The best predictors were microbial biomass and organic layer thickness (Table 3).  Root biomass did not correlate to soil respiration unless 5 other variables were controlled for in a multiple-regression model (Table 4).  Soil temperature did not predict point-to-point variation at this site.
- _Conclusions_: Microbial biomass and organic layer thickness were found to be the best predictors of soil respiration rate.  Root biomass and temperature were found to be unimportant.  The importance of microbial rather than root biomass suggests that ectomycorrhizal fungi rather than plant roots are responsible for much of the root functioning at this site.

-   TREE GIRDLING
- _Goal_: to investigate soil respiration and soil community responses to girdling trees
- Ten lodgepole plots were selected: five were trenched and the enclosed trees girdled before the onset of spring sapflow, five were left as controls.  The goal was to cut off fresh carbon to the soil from trees’ below ground allocation.  Soil respiration rates were measured throughout the subsequent growing season (2002) and the girdled plots saw a marked depression at the summer maximum (Fig. 5).  Microbial biomass and soil soluble carbon content also revealed differing seasonal trends under manipulation (Fig. 6 & 7).  Fungal-bacterial ratios and specific soil community identification will also be done for these plots (in progress).
- _Conclusions_:  Tree-mediated soil respiration accounts for approximately 45% of soil respiration flux.  However, when coupled with previous experiments at this site, it further suggests that ectomycorrhizal fungal respiration could make up a large part of soil respiration at this site.  Soluble carbon concentration seemed to peak during snowmelt in the control plots, but not in the girdled plots.  Microbial biomass seems to be less in the girdled plots, but may have seen a brief enhancement in the early season.

- 3.  PLANT EFFECT INDEX
- _Goal_: to create a proxy for scaling up point measurements of soil respiration rate
- Neither distance to trees nor tree density seemed to adequately predict soil respiration rate in the spatial control experiment.  We therefore tried a composite index for every point (i):
-  Vi = Σ { DBHj/ (dj)2 }
- where DBHj is the diameter of a tree j, dj is the distance to that tree, and V is summed over all trees (j) within a cut-off distance of point i (see Fig. 3). Vi was found to correlate well to soil respiration rate (Fig. 4), but not to other examined variables, such as root biomass.
- _Conclusions_:  A “plant effect” index (V) has been identified that correlates well to soil respiration.  Using a GPS stem-map of the plots, V can be calculated for a grid across the landscape, making an useful proxy for scaling up point measurements of soil respiration rate (in progress).

- DBH1

- DBH3

- DBH2

- DBH4

- d1

- d3

- d2

- d4

- r = 524

**Table 1.**  Summary statistics of a repeated-measures, mixed hierarchical model describing the relationship of soil respiration to covariates soil temperature and soil moisture.  The model treats collars nested within plots and treats time (Julian date) as a continuous variable.

- Acknowledgements: This work was funded wholly or in parts by funds from the National Institute for Global Environmental Change (NIGEC) through the U.S. Department of Energy (Cooperative Agreement No. DE-FCO3-90ER61010).  Any opinions, findings and conclusions or recommendations expressed herein are those of the authors and do not necessarily reflect the views of the DOE.  Thanks to Brant Backlund and Sarah Schliemann for technical assistance.

**Table 2.**  Summary of measured parameters relevant to soil respiration at the Niwot Ridge Ameriflux site.

**Table 3**. Correlation matrix.  Values are correlation coefficients (r). Significance is shown by colors, see key.  Uncolored cells are not significant.

**Table 4.**  Parameter descriptions of multiple regression model of collar-to-collar variation in soil respiration rate.  r2 = 0.4963;  F = 5.747;  df = 6 and 35;  p = 0.0003

- *Error bars are standard error

**Fig. 1**

- Fig. 2

- Fig. 3

- Fig. 1

- Fig. 4

- Fig. 5

- Fig. 6

- Fig. 7