Root Biomass Distribution and Soil Physical Properties of Short-Rotation Coppice American Sycamore (Platanus occidentalis L.) Grown at Different Planting Densities

Short rotation woody crops (SRWCs) provide sustainable, renewable biomass energy and offer potential ecosystem services, including increased carbon storage, reduced greenhouse gas emissions, and improved soil health. Establishing SRWCs on degraded lands has potential to enhance soil properties through root and organic matter turnover. A better understanding of SRWC planting density and its associated root turnover impacts on soil–air–water relations can improve management. In this study, we investigate the effects of planting density for a low-input American sycamore SRWC (no fertilization/irrigation) on soil physical properties for a degraded agricultural site in the North Carolina piedmont. The objectives were (1) to estimate the distributions of coarse and fine root biomass in three planting densities (10,000, 5000, and 2500 trees per hectare (tph)) and (2) to assess the effects of planting density on soil hydraulic properties and pore size distribution. Our results show that planting at 10,000 tph produced significantly higher amounts of fine root biomass than at lower planting densities (p < 0.01). In the 25,000 tph plots, there was significantly higher amounts of coarse root biomass than for higher planting densities (p < 0.05). The 10,000 tph plots had lower plant available water capacity but larger drainable porosity and saturated hydraulic conductivity compared with lower planting densities (<0.05). The 10,000 tph plots total porosity was more dominated by larger pore size fractions compared with the 5000 and 2500 tph. Generally, our findings show similar patterns of soil hydraulic properties and pore size distributions for lower planting densities. The results from 10,000 tph indicate a higher air-filled pore space at field capacity and more rapid drainage compared with lower planting densities. Both characteristics observed in the 10,000 tph are favorable for aeration and oxygen uptake, which are especially important at wet sites. Overall, the results suggest that improved soil health can be achieved from the establishment of American sycamore SRCs on marginal lands, thereby providing a green pathway to achieving environmental sustainability with woody renewable energy.

Application of Machine Learning Techniques to Estimate Unsoaked California Bearing Ratio in Ekiti Central Senatorial District

This paper investigates the relationship between soil physical properties and the Un-soaked California Bearing Ratio (USCBR) of soil found in Ekiti State Central Senatorial District (ESCSD), which includes Natural Moisture Content (NMC%) Percentage Fines, Specific Gravity (SG) and Consistency Limits (LL%, PL%, & PI %). The database was prepared in the laboratory by conducting tests on ninety-nine (99) soil samples which were obtained in a burrowed pit found in the Central Senatorial District of Ekiti State. An R version 4.0.5 and R studio version 1.2.5033 was used to analyze the Artificial Neural Networks (ANNs) and Least Square Regression (LSR) in order to develop a simplified CBR model. In both models, independent layer containing six nodes (soil physical properties) and the dependent layer containing a single node (i.e. CBR) were taken. The descriptive analysis for training and testing was performed; boxplots of the variables were plotted and; sensitivity analysis was carried out. The capacity of the developed equation was evaluated in terms of error metrics MSE and RMSE. The analysis showed that both ANN and MLR models predicted CBR close to the laboratory value. However, the model without the percentage passing sieve 200 (MIC) is the best, having Akaike Information Criterion and Bayesian Information Criterion values of 614.1707 and 627.5754 respectively, from the error metrics analysis, the results showed that PL and LL are the most influential variable that affects the developed CBR model's output. From the foregoing its concluded that the study has shown a relationship between the CBR value of Ekiti Central Senatorial District soil and its basic soils properties using machine learning techniques, also the developed CBR model will be useful tool to Civil engineers, geotechnical engineers and construction industry within the study area particularly in their preliminary stage of their project.

Influence of vegetation structure, seasonality, and soil physical properties on rodent species diversity and community assemblages on West Mount Kilimanjaro, Tanzania.

A study on rodent species diversity and community assemblages in West Mt Kilimanjaro was conducted in seven different habitats, covering two dry and wet seasons. Data were collected using a combination of medium-sized Sherman’s live traps, snap and Havarhart traps, for three consecutive nights. General Linear Models (GLM) were used to analyze the effects of predictors (vegetation attributes, seasonality, soil physical properties, disturbance and altitude) on rodent species richness and abundance. Community structure analysis was conducted in the Primer v6 program and Canonical correspondence analysis for habitat association in PAST. A total of 1,393 individuals from 14 species of rodents were trapped. The most dominant rodent species were Rhabdomys pumilioPraomys delectorum, and Lophuromys verhageni which contributed to 68.86% of the total captures. Lophuromys verhageni occurred across all the habitats and seasons. Moreover, habitat types, seasonality, soil texture, ground cover, and altitude significantly influenced rodent species abundance (P< 0.05). Furthermore, habitat types, seasonality and altitude significantly influenced rodent species richness (F8, 759 = 629.7, p< 0.001, R2 = 0.87). In addition to that, two major rodent communities were formed in different habitats. The results show that rodent species richness, abundance, and community assemblages in Mt Kilimanjaro, are a result of change in vegetation structure along the altitudinal gradients. Therefore, information on habitat requirements of multiple species is crucial for the management and conservation of these communities.