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Title: SOIL CARBON ASSESSMENT ACROSS A NATIVE PRAIRIE RESTORATION CHRONONSEQUENCE

Author
item Cambardella, Cynthia
item ISENHART, T - DNR ECOL & MGT, ISU
item SCHILLING, K - IA DNR GEOL SURVEY BUREAU
item DROBNEY, P - US FISH&WILDLIFE SERVICE
item SCHULTZ, R - DNR ECOL & MGT, ISU

Submitted to: North American Prairie Conference
Publication Type: Proceedings
Publication Acceptance Date: 11/4/2002
Publication Date: 3/3/2004
Citation: Cambardella, C.A., Isenhart, T.M., Schilling, K.E., Drobney, P., Schultz, R.C. 2004. Soil carbon assessment across a native prairie restoration chrononsequence. In: Fore, Stephanie, editor. Proceedings of the 18th North American Prairie Conference, June 23-27, 2002, Kirksville, MO. p. 49-53.

Interpretive Summary: Converting agricultural land to grasslands or forests can result in positive environmental changes in these ecosystems, such as increased water- and nutrient-use efficiency and decreased erosion. Many of these positive changes can be related to increased soil organic matter levels in the restored ecosystems. Knowledge about system changes that occur during and after the transition to native vegetation can be used to develop managed ecosystems that cycle water and nutrients more efficiently. We measured soil organic carbon content in 1-8 year-old reconstructed native tallgrass prairies at Neal Smith National Wildlife Refuge (NSNWR) near Prairie City, IA to determine the effect of time since prairie reestablishment on soil carbon accumulation. We found that soil organic carbon varied in the reconstructed prairies but not in a manner that was consistently related to the length of time since the prairie was re-established. This will impact our ability to consistenetly detect changes in soil organic carbon in the early years following ecosystem restoration. Information gained from this research will useful to scientists interested in evaluating carbon cycling in agricultural land that has been converted to perennial vegetation. Future work in reconstructed ecosystems will focus on developing and implementing methods to improve our ability to detect changes in ecosystem parameters.

Technical Abstract: Native tallgrass prairie ecosystems allocate a large percentage of photosynthetically-fixed carbon below ground. Restoring disturbed prairie systems to the native state can potentially result in large increases in soil carbon. This study focused on quantifying soil profile carbon at Neal Smith National Wildlife Refuge (NSNWR) near Prairie City, IA to determine the effect of time since prairie reestablishment on soil carbon accumulation. Blocks of land have been restored to native prairie at NSNWR every year since 1993. We used a stratified sampling design to identify sampling locations within 6 restored areas, 3 native remnant areas, and 2 cultivated areas blocked by 3 upland soil types. Geographic Information System (GIS) coverages of all possible sampling locations were created and an Arcview area grid and random number generator were used to select exact sampling locations. Global Positioning System (GPS) coordinates were used to locate sampling sites in the field. Soil cores were collected in May of 2000 to a depth of 120 cm using a truck-mounted or modified, hand-held Giddings soil sampler. Total soil carbon to a depth of 120 cm averaged across all sites ranged from 77.9 to 105.5 Mg C ha-1. Coefficients of variation ranged from 3 to 46%. We didn't observe a consistent positive change in soil carbon contents in the prairie restoration chronosequence with time since restoration. Cultivated or remnant sites didn't have consistently less or more soil carbon than restored sites. Variability was relatively high despite the stratified design. Landscape-scale changes in total soil carbon are difficult to detect over the short term, primarily due to landscape-scale spatial heterogeneity in soil carbon contents and inconsistent impacts of historic management practices on current soil carbon stocks. Future work at the refuge will focus on minimizing these problems in order to optimize our ability to detect changes in ecosystem parameters.