3 resultados para Sampling time
em Digital Commons - Michigan Tech
Resumo:
The amount and type of ground cover is an important characteristic to measure when collecting soil disturbance monitoring data after a timber harvest. Estimates of ground cover and bare soil can be used for tracking changes in invasive species, plant growth and regeneration, woody debris loadings, and the risk of surface water runoff and soil erosion. A new method of assessing ground cover and soil disturbance was recently published by the U.S. Forest Service, the Forest Soil Disturbance Monitoring Protocol (FSDMP). This protocol uses the frequency of cover types in small circular (15cm) plots to compare ground surface in pre- and post-harvest condition. While both frequency and percent cover are common methods of describing vegetation, frequency has rarely been used to measure ground surface cover. In this study, three methods for assessing ground cover percent (step-point, 15cm dia. circular and 1x5m visual plot estimates) were compared to the FSDMP frequency method. Results show that the FSDMP method provides significantly higher estimates of ground surface condition for most soil cover types, except coarse wood. The three cover methods had similar estimates for most cover values. The FSDMP method also produced the highest value when bare soil estimates were used to model erosion risk. In a person-hour analysis, estimating ground cover percent in 15cm dia. plots required the least sampling time, and provided standard errors similar to the other cover estimates even at low sampling intensities (n=18). If ground cover estimates are desired in soil monitoring, then a small plot size (15cm dia. circle), or a step-point method can provide a more accurate estimate in less time than the current FSDMP method.
Resumo:
The herbaceous layer is a dynamic layer in a forest ecosystem which often contains the highest species richness in northern temperate forests. Few long-term studies exist in northern hardwood forests with consistent management practices to observe herbaceous species dynamics. The Ford Forest (Michigan Technological University) reached its 50th year of management during the winter of 2008-2009. Herbaceous species were sampled during the summers pre- and post-harvest. Distinct herbaceous communities developed in the 13-cm diameter-limit treatment and the uncut control. After the harvest, the diameter-limit treatments had herbaceous communities more similar to the 13-cm diameter-limit treatment than the uncut control; the herbaceous layer contained more exotic and early successional species. Fifty years of continuous management changed the herbaceous community especially in the diameter-limit treatments. Sites used in the development of habitat classification systems based on the presence and absence of certain herbaceous species can also be used to monitor vegetation change over time. The Guide to Forest Communities and Habitat Types of Michigan was developed to aid forest managers in understanding the potential productivity of a stand, and often aid in the development of ecologically-based forest management practices. Subsets of plots used to create the Western Upper Peninsula Guide were resampled after 10 years. During the resampling, both spring and summer vegetation were sampled and earthworm populations were estimated through liquid extraction. Spring sampling observed important spring ephemerals missed during summer sampling. More exotic species were present during the summer 2010 sampling than the summer 2000 sampling. Invasive European earthworms were also observed at all sample locations in all habitat types; earthworm densities increased with increasing habitat richness. To ensure the accuracy of the guide book, plots should be monitored to see how herbaceous communities are changing. These plots also offer unique opportunities to monitor for invasive species and the effects of a changing climate.
Resumo:
Traditionally, densities of newly built roadways are checked by direct sampling (cores) or by nuclear density gauge measurements. For roadway engineers, density of asphalt pavement surfaces is essential to determine pavement quality. Unfortunately, field measurements of density by direct sampling or by nuclear measurement are slow processes. Therefore, I have explored the use of rapidly-deployed ground penetrating radar (GPR) as an alternative means of determining pavement quality. The dielectric constant of pavement surface may be a substructure parameter that correlates with pavement density, and can be used as a proxy when density of asphalt is not known from nuclear or destructive methods. The dielectric constant of the asphalt can be determined using ground penetrating radar (GPR). In order to use GPR for evaluation of road surface quality, the relationship between dielectric constants of asphalt and their densities must be established. Field measurements of GPR were taken at four highway sites in Houghton and Keweenaw Counties, Michigan, where density values were also obtained using nuclear methods in the field. Laboratory studies involved asphalt samples taken from the field sites and samples created in the laboratory. These were tested in various ways, including, density, thickness, and time domain reflectometry (TDR). In the field, GPR data was acquired using a 1000 MHz air-launched unit and a ground-coupled unit at 200 and 500 MHz. The equipment used was owned and operated by the Michigan Department of Transportation (MDOT) and available for this study for a total of four days during summer 2005 and spring 2006. The analysis of the reflected waveforms included “routine” processing for velocity using commercial software and direct evaluation of reflection coefficients to determine a dielectric constant. The dielectric constants computed from velocities do not agree well with those obtained from reflection coefficients. Perhaps due to the limited range of asphalt types studied, no correlation between density and dielectric constant was evident. Laboratory measurements were taken with samples removed from the field and samples created for this study. Samples from the field were studied using TDR, in order to obtain dielectric constant directly, and these correlated well with the estimates made from reflection coefficients. Samples created in the laboratory were measured using 1000 MHz air-launched GPR, and 400 MHz ground-coupled GPR, each under both wet and dry conditions. On the basis of these observations, I conclude that dielectric constant of asphalt can be reliably measured from waveform amplitude analysis of GJPR data, based on the consistent agreement with that obtained in the laboratory using TDR. Because of the uniformity of asphalts studied here, any correlation between dielectric constant and density is not yet apparent.