The long-term effects of whole-tree harvest at final felling on soil properties in a Norway Spruce (Picea Abies (L) Karst.) Stand

Increased demand for forest-derived biomass has resulted in changes in harvest intensities in Finland. Conventional stem-only harvest (CH) has to some extent been replaced with whole-tree harvest (WTH). The latter involves a greater removal of nutrients from the forest ecosystem, as all the above ground biomass is exported from the site. This has raised concerns that WTH could result in large changes in the nutrient dynamics of a forest stand and could eventually lower its site productivity. Little empirical data exists to support this assumption as only a limited number of studies have been conducted on the topic. A majority of these discuss the short-term effects, thus the long-term consequences remain unknown. The objective of this study was to compare differences in soil properties after CH and WTH in a fertile Norway spruce (Picea abies (L) Karst.) stand in Southern Finland. The site was clear-felled in August 2000 and spruce seedlings were planted in the following summer. Soil sampling in the form of systematic randomized sampling was carried out in May 2011. Changes in base saturation, cation exchange capacity, elemental pools (total and exchangeable) and acidity were studied in both organic and mineral horizons. The results indicate that WTH lowered effective cation exchange capacity and base saturation particularly in the humus layer. The pools of exchangeable Al and Fe were increased in the humus layer, whereas the amount of exchangeable Ca decreased in both layers. WTH also resulted in lower Ca/Al-ratios across the sampled layers. Treatment did not have a significant effect on pH, total pools of elements or on the C/N-ratio of the soil. The results suggest that although the stand possesses significant pools of nutrients at present, WTH, if continued, could have long-term effects on site productivity.

SAMPLING BIAS IN EVALUATING THE PROBABILITY OF SEISMICALLY INDUCED SOIL LIQUEFACTION WITH SPT & CPT CASE HISTORIES

Several deterministic and probabilistic methods are used to evaluate the probability of seismically induced liquefaction of a soil. The probabilistic models usually possess some uncertainty in that model and uncertainties in the parameters used to develop that model. These model uncertainties vary from one statistical model to another. Most of the model uncertainties are epistemic, and can be addressed through appropriate knowledge of the statistical model. One such epistemic model uncertainty in evaluating liquefaction potential using a probabilistic model such as logistic regression is sampling bias. Sampling bias is the difference between the class distribution in the sample used for developing the statistical model and the true population distribution of liquefaction and non-liquefaction instances. Recent studies have shown that sampling bias can significantly affect the predicted probability using a statistical model. To address this epistemic uncertainty, a new approach was developed for evaluating the probability of seismically-induced soil liquefaction, in which a logistic regression model in combination with Hosmer-Lemeshow statistic was used. This approach was used to estimate the population (true) distribution of liquefaction to non-liquefaction instances of standard penetration test (SPT) and cone penetration test (CPT) based most updated case histories. Apart from this, other model uncertainties such as distribution of explanatory variables and significance of explanatory variables were also addressed using KS test and Wald statistic respectively. Moreover, based on estimated population distribution, logistic regression equations were proposed to calculate the probability of liquefaction for both SPT and CPT based case history. Additionally, the proposed probability curves were compared with existing probability curves based on SPT and CPT case histories.

A comparison of ground cover and frequency estimation methods for post-harvest soil monitoring

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.

Modeling and classifying variable width riparian zones utilizing digital elevation models, flood height data, digital soil data and national wetlands inventory : a new approach for riparian zone delineation

Riparian zones are dynamic, transitional ecosystems between aquatic and terrestrial ecosystems with well defined vegetation and soil characteristics. Development of an all-encompassing definition for riparian ecotones, because of their high variability, is challenging. However, there are two primary factors that all riparian ecotones are dependent on: the watercourse and its associated floodplain. Previous approaches to riparian boundary delineation have utilized fixed width buffers, but this methodology has proven to be inadequate as it only takes the watercourse into consideration and ignores critical geomorphology, associated vegetation and soil characteristics. Our approach offers advantages over other previously used methods by utilizing: the geospatial modeling capabilities of ArcMap GIS; a better sampling technique along the water course that can distinguish the 50-year flood plain, which is the optimal hydrologic descriptor of riparian ecotones; the Soil Survey Database (SSURGO) and National Wetland Inventory (NWI) databases to distinguish contiguous areas beyond the 50-year plain; and land use/cover characteristics associated with the delineated riparian zones. The model utilizes spatial data readily available from Federal and State agencies and geospatial clearinghouses. An accuracy assessment was performed to assess the impact of varying the 50-year flood height, changing the DEM spatial resolution (1, 3, 5 and 10m), and positional inaccuracies with the National Hydrography Dataset (NHD) streams layer on the boundary placement of the delineated variable width riparian ecotones area. The result of this study is a robust and automated GIS based model attached to ESRI ArcMap software to delineate and classify variable-width riparian ecotones.