A probabilistic approach may be adopted to predict freeze and thaw depths to account for the variability of (1) material properties, and (2) contemporary and future surface energy input parameters (e.g. air temperatur...A probabilistic approach may be adopted to predict freeze and thaw depths to account for the variability of (1) material properties, and (2) contemporary and future surface energy input parameters (e.g. air temperatures, cloud cover, snow cover) predicted with global climate models. To illustrate the probabilistic approach, an example of the prediction of thaw depths in Fairbanks, Alaska, is considered. More specifically, the Stefan equation is used together with the Monte Carlo simulation technique to make a probabilistic prediction of thaw penetration. The simulation results indicate that the variability in material properties, surface energy input parameters, and temperature data can lead to significant uncertainty in predicting thaw penetration. The Taylor series method was performed to determine the mean and standard deviation of thaw penetration and the results were compared to the Monte Carlo simulation results. The close comparison of the results suggests that the simpler Taylor series method may be applied to many cold regions problems to account for the variability of input parameters.展开更多
Soil samples at 0-10 cm in depth were collected periodically at paired fields in Corvallis, Oregon, USA to compare differences in soil microbial and faunal populations between organic and conventional agroecosystems. ...Soil samples at 0-10 cm in depth were collected periodically at paired fields in Corvallis, Oregon, USA to compare differences in soil microbial and faunal populations between organic and conventional agroecosystems. Results showed that the organic soil ecosystem had a significantly higher (P < 0.05) average number or biomass of soil bacteria; densities of flagellates, amoebae of protozoa; some nematodes, such as microbivorous and predaceous nematodes and plant-parasitic nematodes; as well as Collembola. Greater numbers of Rhabditida (such as Rhabditis spp.), were present in the organic soil ecosystem while Panagrolaimus spp. were predominant in the conventional soil ecosystem. The omnivores and predators of Acarina in the Mesostigmata (such as Digamasellidae and Laelapid), and Prostigmata (such as Alicorhaiidae and Rhagidiidae), were also more abundant in the organic soil ecosystem. However, fungivorous Prostigmata (such as Terpnacaridae and Nanorchestidae) and Astigmata (such as Acarida) were significantly higher (P < 0.05) in the conventional soil ecosystem, which supported the finding that total fungal biomass was greater in the conventional soil ecosystem. Seansonal variations of the population depended mostly on soil moisture condition and food web relationship. The population declined from May to October for both agroecosystems. However, higher diversities and densities of soil biota survived occurred in the organic soil ecosystem in the dry season.展开更多
文摘A probabilistic approach may be adopted to predict freeze and thaw depths to account for the variability of (1) material properties, and (2) contemporary and future surface energy input parameters (e.g. air temperatures, cloud cover, snow cover) predicted with global climate models. To illustrate the probabilistic approach, an example of the prediction of thaw depths in Fairbanks, Alaska, is considered. More specifically, the Stefan equation is used together with the Monte Carlo simulation technique to make a probabilistic prediction of thaw penetration. The simulation results indicate that the variability in material properties, surface energy input parameters, and temperature data can lead to significant uncertainty in predicting thaw penetration. The Taylor series method was performed to determine the mean and standard deviation of thaw penetration and the results were compared to the Monte Carlo simulation results. The close comparison of the results suggests that the simpler Taylor series method may be applied to many cold regions problems to account for the variability of input parameters.
文摘Soil samples at 0-10 cm in depth were collected periodically at paired fields in Corvallis, Oregon, USA to compare differences in soil microbial and faunal populations between organic and conventional agroecosystems. Results showed that the organic soil ecosystem had a significantly higher (P < 0.05) average number or biomass of soil bacteria; densities of flagellates, amoebae of protozoa; some nematodes, such as microbivorous and predaceous nematodes and plant-parasitic nematodes; as well as Collembola. Greater numbers of Rhabditida (such as Rhabditis spp.), were present in the organic soil ecosystem while Panagrolaimus spp. were predominant in the conventional soil ecosystem. The omnivores and predators of Acarina in the Mesostigmata (such as Digamasellidae and Laelapid), and Prostigmata (such as Alicorhaiidae and Rhagidiidae), were also more abundant in the organic soil ecosystem. However, fungivorous Prostigmata (such as Terpnacaridae and Nanorchestidae) and Astigmata (such as Acarida) were significantly higher (P < 0.05) in the conventional soil ecosystem, which supported the finding that total fungal biomass was greater in the conventional soil ecosystem. Seansonal variations of the population depended mostly on soil moisture condition and food web relationship. The population declined from May to October for both agroecosystems. However, higher diversities and densities of soil biota survived occurred in the organic soil ecosystem in the dry season.
