5 resultados para Soil conditions

em Digital Commons - Michigan Tech


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Assessment of soil disturbance on the Custer National Forest was conducted during two summers to determine if the U.S. Forest Service Forest Soil Disturbance Monitoring Protocol (FSDMP) was able to distinguish post-harvest soil conditions in a chronological sequence of sites harvested using different ground-based logging systems. Results from the first year of sampling suggested that the FSDMP point sampling method may not be sensitive enough to measure post-harvest disturbance in stands with low levels of disturbance. Therefore, a revised random transect method was used during the second sampling season to determine the actual extent of soil disturbance in these cutting units. Using combined data collected from both summers I detected statistically significant differences (p < 0.05) in fine fraction bulk density measurements between FSDMP disturbance classes across all sites. Disturbance class 3 (most severe) had the highest reported bulk density, which suggest that the FSDMP visual class estimates are defined adequately allowing for correlations to be made between visual disturbance and actual soil physical characteristics. Forest site productivity can be defined by its ability to retain carbon and convert it to above- and belowground biomass. However, forest management activities that alter basic site characteristics have the potential to alter productivity. Soil compaction is one critical management impact that is important to understand; compaction has been shown to impede the root growth potential of plants, reduce water infiltration rates increasing erosion potential, and alter plant available water and nutrients, depending on soil texture. A new method to assess ground cover, erosion, and other soil disturbances was recently published by the U.S. Forest Service, as the Forest Soil Disturbance Protocol (FSDMP). The FSDMP allows soil scientists to visually assign a disturbance class estimate (0 – none, 1, 2, 3 – severe) from field measures of consistently defined soil disturbance indicators (erosion, fire, rutting, compaction, and platy/massive/puddled structure) in small circular (15 cm) plots to compare soil quality properties pre- and post- harvest condition. Using this protocol we were able to determine that ground-based timber harvesting activities occurring on the Custer National Forest are not reaching the 15% maximum threshold for detrimental soil disturbance outlined by the Region 1 Soil Quality Standards.

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Organic amendments are commonly used to improve tree nursery soil conditions for increased seedling growth. However, few studies compare organic amendments effects on soil conditions, and fewer compare subsequent effects on seedling growth. The effects of three organic amendments on soil properties and seedling growth were investigated at the USDA Forest Service J.W. Toumey Nursery in Watersmeet, MI. Pine sawdust (red pine, Pinus resinosa), hardwood sawdust (maple, Acer spp. and aspen, Populus spp.), and peat were individually incorporated into a loamy sand nursery soil in August, 2006, and soil properties were sampled periodically for the next 14 months. Jack (Pinus banksiana), red, and white pine (Pinus strobus) were sown into test plots in June, 2007 and sampled for growth responses at the end of the growing season. It is hypothesized; pine sawdust and peat can be used as a satisfactory soil amendment to improve soil conditions and produce high quality seedlings, when compared to hardwood sawdust in bareroot nursery soils. This study has the potential to reduce nursery costs while broadening soil amendment options. The addition of peat and pine sawdust increased soil organic matter above control soil conditions after 14 months. However, hardwood sawdust-amended soils did not differ from control soils after same time period. High N concentrations in peat increased total soil N over the other treatments. Similarly, the addition of peat increased soil matric potential and available water over all other treatments. Seedlings grew tallest with the largest stem diameter, and had the largest biomass in both control soil and soil amended with peat, compared to either sawdust treatment. Seedlings grown in peat-amended soils had higher N concentrations than those grown in soils treated with pine sawdust, though neither was different from seedlings grown in control or hardwood sawdust-amended soils. Overall, peat is a well suited organic soil amendment for the enhancement of soil properties, but no amendments were able to increase one-year seedling growth over control soils.

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Global climate change might significantly impact future ecosystems. The purpose of this thesis was to investigate potential changes in woody plant fine root respiration in response to a changing climate. In a sugar maple dominated northern hardwood forest, the soil was experimentally warmed (+4 °C) to determine if the tree roots could metabolically acclimate to warmer soil conditions. After one and a half years of soil warming, there was an indication of slight acclimation in the fine roots of sugar maple, helping the ecosystem avoid excessive C loss to the atmosphere. In a poor fen northern peatland in northern Michigan, the impacts of water level changes on woody plant fine root respiration were investigated. In areas of increased and also decreased water levels, there were increases in the CO2 efflux from ecosystem fine root respiration. These studies show the importance of investigating further the impacts climate change may have on C balance in northern ecosystems.

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Globally, peatlands occupy a small portion of terrestrial land area but contain up to one-third of all soil organic carbon. This carbon pool is vulnerable to increased decomposition under projected climate change scenarios but little is known about how plant functional groups will influence microbial communities responsible for regulating carbon cycling processes. Here we examined initial shifts in microbial community structure within two sampling depths under plant functional group manipulations in mesocosms of an oligotrophic bog. Microbial community composition for bacteria and archaea was characterized using targeted 16S rRNA Illumina gene sequencing. We found statistically distinct spatial patterns between the more shallow 10-20 cm sampling depth and the deeper 30-40 cm depth. Significant effects by plant functional groups were found only within the 10-20 cm depth, indicating plant-mediated microbial community shifts respond more quickly near the peat surface. Specifically, the relative abundance of Acidobacteria decreased under ericaceous shrub treatments in the 10-20 cm depth and was replaced by increased abundance of Gammaproteobacteria and Bacteroidetes. In contrast, the sedge rhizosphere continued to be dominated by Acidobacteria but also promoted an increase in the relative recovery of Alphaproteobacteria and Verrucomicrobia. These initial results suggest microbial communities under ericaceous shrubs may be limited by anaerobic soil conditions accompanying high water table conditions, while sedge aerenchyma may be promoting aerobic taxa in the upper peat rhizosphere regardless of ambient soil oxygen limitations.

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Global climate change is predicted to have impacts on the frequency and severity of flood events. In this study, output from Global Circulation Models (GCMs) for a range of possible future climate scenarios was used to force hydrologic models for four case study watersheds built using the Soil and Water Assessment Tool (SWAT). GCM output was applied with either the "delta change" method or a bias correction. Potential changes in flood risk are assessed based on modeling results and possible relationships to watershed characteristics. Differences in model outputs when using the two different methods of adjusting GCM output are also compared. Preliminary results indicate that watersheds exhibiting higher proportions of runoff in streamflow are more vulnerable to changes in flood risk. The delta change method appears to be more useful when simulating extreme events as it better preserves daily climate variability as opposed to using bias corrected GCM output.