scholarly journals Influence of Mine Soil Properties on White Oak Seedling Growth: A Proposed Mine Soil Classification Model

2007 ◽  
Vol 31 (2) ◽  
pp. 99-107 ◽  
Author(s):  
Julia M. Showalter ◽  
James A. Burger ◽  
Carl E. Zipper ◽  
John M. Galbraith ◽  
Patricia F. Donovan
Keyword(s):  
Regression Model ◽  
Soil Properties ◽  
Seedling Growth ◽  
Tree Growth ◽  
Tree Height ◽  
Soil Classification ◽  
Classification Model ◽  
Slope Aspect ◽  
Mine Soil ◽  
White Oak

Abstract Appalachian landowners are becoming increasingly interested in restoring native hardwood forest on reclaimed mined land. Trees are usually planted in topsoil substitutes consisting of blasted rock strata, and reforestation attempts using native hardwoods are often unsuccessful due to adverse soil properties. The purpose of this study was to determine which mine soil properties most influence white oak (Quercus alba L.) seedling growth, and to test whether these properties are reflected adequately in a proposed mine soil classification model developed for application in field assessments of mine soil suitability for reforestation. Seventy-two 3-year-old white oaks were randomly selected across a reclaimed site in southwestern Virginia that varied greatly in spoil/site properties. Tree height was measured and soil samples adjacent to each tree were analyzed for physical, chemical, and biological properties. Our proposed mined land classification model used rock type, compaction, and slope aspect as mapping criteria. Tree height, ranging from 15.2 to 125.0 cm, was regressed against mine soil and site properties. Mapping units were not well correlated with differences in tree height. Microbial biomass, pH, exchangeable potassium, extractable inorganic nitrogen, texture, aspect, and extractable phosphorous accounted for 52% of the variability in tree growth. The regression model shows that white oaks were most successful on northeast-facing aspects, in slightly acidic, sandy loam, fertile mine soils that are conducive to microbial activity. Nutrient availability, although found to be highly influential on tree growth, was not adequately represented in the classification model. We recommend that pH be included as a classification criterion, because it was correlated with all nutrient variables in the regression model.

INFLUENCE OF PHYSICAL, CHEMICAL, AND BIOLOGICAL MINE SOIL PROPERTIES ON WHITE OAK SEEDLING GROWTH

2005 ◽  
Vol 2005 (1) ◽  
pp. 1029-1041
Author(s):  
J. M. Showalter ◽  
◽  
J. A. Burger ◽  
C. E. Zipper ◽  
J. M. Galbraith
Keyword(s):  
Soil Properties ◽  
Seedling Growth ◽  
Mine Soil ◽  
White Oak ◽  
Physical Chemical

scholarly journals Early Tree Growth in Reclaimed Mine Soils in Appalachia USA

Forests ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 549 ◽  
Author(s):  
Kara Dallaire ◽  
Jeffrey Skousen
Keyword(s):  
Tree Growth ◽  
Forest Soils ◽  
Rooting Depth ◽  
Red Oak ◽  
Native Forest ◽  
Mine Soils ◽  
Mine Soil ◽  
White Oak ◽  
Native Soils ◽  
Tulip Poplar

Surface mining disturbs hundreds of hectares of land every year in many areas of the world, thereby altering valuable, ecologically-diverse forests. Reforestation of these areas after mining helps to restore ecosystem functions and land value. In Appalachia, native topsoil is normally replaced on the surface during reclamation, but waivers allow for brown and gray sandstone materials to be used as topsoil substitutes. Numerous studies report the growth of trees in these substitute mine soil materials, but few studies have compared the height of trees grown in reclaimed mine soils to the heights of trees grown in native soils. This study determined the growth of red oak (Q. rubra L.), white oak (Quercus alba L.), and tulip poplar (Liriodendron tulipifera L.) in two mine soil types which were compared to projected growth in native soils. Heights of tree seedlings in native soils at 11 years were estimated from site indices (SI) from USDA Soil Survey data. At the mine sites, areas with brown and gray mine soils (one site with a mulch treatment) had 12 tree species planted and growth was measured annually for 11 years. Mine soil pH after 11 years was 5.3 for brown mine soils, 6.6 for gray mine soils, 7.0 for mulched mine soils, and 4.1 to 5.2 for native forest soils. After 11 years, tree heights in gray mine soils were significantly lower (0.5 m) than tree heights in brown mine soils (2.8 to 4 m) for all three species. Trees in mulched mine soils were up to 0.7 m taller than trees in un-mulched brown mine soils. After 11 years, red oak height was 6.3 m in native soils and 3 m in brown and mulched mine soils (52% lower); white oak was 7.3 m tall in native soils compared to 3.6 m in brown mine soils (50% lower); and tulip poplar was 11.5 m tall in native soils and 3.5 to 4 m tall in brown and mulched mine soils (70% lower). In gray mine soils, trees were not growing at all. While the trees in brown mine soils are growing, tree growth has not reached projected levels of tree growth in native soils during the first 11 years after planting. The purpose of forestry reclamation is to restore ecosystem diversity and function. This study showed that one measure of ecosystem function, tree growth, was 50% lower on reclaimed mine soils than native forest soils. Maturing mine soils may develop properties over time that are similar to native soils and, with the increased rooting depth, may provide conditions where increased tree growth rates and height may be attained during the next several decades.

Correlation of pH on Soil Physicochemical Properties using Linear Regression Model for Spectral Data Analysis

2021 ◽  
Vol 10 (1) ◽  
pp. 3492-3500
Author(s):  
Vipin Y. Borole ◽  
◽  
Sonali B. Kulkarni ◽  
Keyword(s):  
Linear Regression ◽  
Plant Growth ◽  
Physicochemical Properties ◽  
Regression Model ◽  
Soil Properties ◽  
Spectral Data ◽  
Linear Regression Model ◽  
Soil Analysis ◽  
Soil Physicochemical Properties ◽  
Analytical Technique

Soil properties may be varied by spatially and temporally with different agricultural practices. An accurate and reliable soil properties assessment is challenging issue in soil analysis. The soil properties assessment is very important for understanding the soil properties, nutrient management, influence of fertilizers and relation between soil properties which are affecting the plant growth. Conventional laboratory methods used to analyses soil properties are generally impractical because they are time-consuming, expensive and sometimes imprecise. On other hand, Visible and infrared spectroscopy can effectively characterize soil. Spectroscopic measurements are rapid, precise and inexpensive. Soil spectroscopy has shown to be a fast, cost-effective, environmentally friendly, non-destructive, reproducible and repeatable analytical technique. In the present research, we use spectroscopy techniques for soil properties analysis. The spectra of agglomerated farming soils were acquired by the ASD Field spec 4 spectroradiometer. Different fertilizers treatment applied soil samples are collected in pre monsoon and post monsoon season for 2 year (4 season) for banana and cotton crops in the form of DS-I and DS-II respectively. The soil spectra of VNIR region were preprocessed to get pure spectra. Then process the acquired spectral data by statistical methods for quantitative analysis of soil properties. The detected soil properties were carbon, Nitrogen, soil organic matter, pH, phosphorus, potassium, moisture sand, silt and clay. Soil pH is most important chemical properties that describe the relative acidity or alkalinity of the soil. It directly effect on plant growth and other soil properties. The relationship between pH properties on soil physical and chemical parameters and their influence were analyses by using linear regression model and show the performance of regression model with R2 and RMSE. Keywords soil; physicochemical properties; spectroscopy; pH

Soil properties and growth of swamp white oak and pin oak on bedded soils in the lower Missouri River floodplain

2005 ◽  
Vol 204 (2-3) ◽  
pp. 315-327 ◽  
Author(s):  
John M. Kabrick ◽  
Daniel C. Dey ◽  
J.W. Van Sambeek ◽  
Michael Wallendorf ◽  
Michael A. Gold
Keyword(s):  
Soil Properties ◽  
Missouri River ◽  
White Oak ◽  
River Floodplain ◽  
Swamp White Oak

scholarly journals Direct and indirect effects of environmental limitations on white spruce xylem anatomy at treeline

2021 ◽  
Author(s):  
Timo Pampuch ◽  
Mario Trouillier ◽  
Alba Anadon-Rosell ◽  
Jelena Lange ◽  
Martin Wilmking
Keyword(s):  
Tree Growth ◽  
Environmental Conditions ◽  
Indirect Effects ◽  
Tree Height ◽  
White Spruce ◽  
Vegetation Period ◽  
Lumen Diameter ◽  
Xylem Anatomy ◽  
Direct And Indirect Effects ◽  
Mixed Effect

<p>Treeline ecosystems are of great scientific interest to study the direct and indirect influence of limiting environmental conditions on tree growth. However, tree growth is complex and multidimensional, and its responses to the environment depend on a large number of abiotic and biotic factors and their interactions.</p><p>In this study, we analyze the growth and xylem anatomy of white spruce trees (<em>Picea glauca</em> [Moench] Voss) from three treelines in Alaska (one warm and drought-limited, and two cold and temperature-limited treelines). We hypothesized (1) no difference between the treelines regarding the relationship between tree DBH and height, yet in general (2) faster growing trees at the warmer site. Additionally, we expected to find differences in xylem anatomical traits with trees from the drought-limited site having adapted to drought conditions by (3) forming smaller lumen diameter due to water deficit but (4) a higher xylem anatomical density due to higher temperatures and a longer vegetation period.</p><p>Regarding growth in height and diameter, trees at the drought-limited treeline grew relatively (1) taller and (2) faster compared to trees at the temperature-limited treelines. Raw xylem anatomical measurements showed (3) smaller lumen diameters and (4) higher density in trees at the drought-limited treeline. However, using linear mixed-effect models, we found that (i) traits related to water transport like lumen diameter were not significantly correlated with the actual amount of precipitation during the vegetation period but with tree height. We also found that (ii) traits related to mechanical support like density were mainly positively influenced by the mean temperature during the vegetation period.</p><p>The differences in lumen diameter found in the raw data can be explained by differences in the growth rates of the trees, since lumen diameter at the lower part of the tree stem needs to increase over time with increasing tree height. The greater wood density at the drought-limited treeline is probably caused by the higher temperature that leads to more biomass production, and potentially longer vegetation periods.</p><p>Our study shows that xylem anatomical traits in white spruce can be directly and indirectly controlled by environmental conditions. While lumen diameter is not directly influenced by environmental conditions but indirectly through tree height, other traits like anatomical density show a direct correlation with environmental conditions. Our results highlight the importance of approaching tree growth in a multidimensional way and considering direct and indirect effects of environmental forcing.</p>

scholarly journals Identification of distinct characteristics of antibiofilm peptides and prospection of diverse sources for efficacious sequences

2021 ◽  
Author(s):  
Bipasa Bose ◽  
Taylor Downey ◽  
Anand K. Ramasubramanian ◽  
David C. Anastasiu
Keyword(s):  
Regression Model ◽  
Sequence Similarity ◽  
Drug Repurposing ◽  
Classification Model ◽  
Antibiofilm Activity ◽  
High Sequence Similarity ◽  
Small Molecule Drugs ◽  
Microbial Infections ◽  
Positive Dataset ◽  
Therapeutic Properties

A majority of microbial infections are associated with biofilms. Targeting biofilms is considered an effective strategy to limit microbial virulence while minimizing the development of antibiotic resistance. Towards this need, antibiofilm peptides are an attractive arsenal since they are bestowed with properties orthogonal to small molecule drugs. In this work, we developed machine learning models to identify the distinguishing characteristics of known antibiofilm peptides, and to mine peptide databases from diverse habitats to classify new peptides with potential antibiofilm activities. Additionally, we used the reported minimum inhibitory/eradication concentration (MBIC/MBEC) of the antibiofilm peptides to create a regression model on top of the classification model to predict the effectiveness of new antibiofilm peptides. We used a positive dataset containing 242 antibiofilm peptides, and a negative dataset which, unlike previous datasets, contains peptides that are likely to promote biofilm formation. Our model achieved a classification accuracy greater than 98% and harmonic mean of precision-recall (F1) and Matthews correlation coefficient (MCC) scores greater than 0.90; the regression model achieved an MCC score greater than 0.81. We utilized our classification-regression pipeline to evaluate 135,015 peptides from diverse sources and identified antibiofilm peptide candidates that are efficacious against preformed biofilms at micromolar concentrations. Structural analysis of the top 37 hits revealed a larger distribution of helices and coils than sheets. Sequence alignment of these hits with known antibiofilm peptides revealed that, while some of the hits showed relatively high sequence similarity with known peptides, some others did not indicate the presence of antibiofilm activity in novel sources or sequences. Further, some of the hits had previously recognized therapeutic properties or host defense traits suggestive of drug repurposing applications. Taken together, this work demonstrates a new in silicio approach to predicting antibiofilm efficacy, and identifies promising new candidates for biofilm eradication.

scholarly journals Hierarchical Environmental Factors Affecting the Distribution of Abies koreana on the Korean Peninsula

2018 ◽  
Author(s):  
Jeong Soo Park ◽  
Hak Sub Shin ◽  
Chul-hyun Choi ◽  
Jinhee Kim ◽  
Junghyo Lee
Keyword(s):  
Environmental Factors ◽  
Regression Model ◽  
Korean Peninsula ◽  
Spatial Scales ◽  
Weather Conditions ◽  
Winter Precipitation ◽  
Slope Aspect ◽  
Dwarf Bamboo ◽  
Abies Koreana ◽  
Korean Fir

Regional declines of the Korean fir (Abies koreana) have been observed since the 1980s on the subalpine region. To explain this decline, it is fundamental to investigate the degree to which environmental factors have contributed to plant distributions on diverse spatial scales. We applied a hierarchical regression model to determine quantitatively the relationship between the abundance of Korean fir (seedlings) and diverse environmental factors across two different ecological scales. We measured Korean fir density and the occurrence of its seedlings in 102 (84) plots nested at five sites and collected a range of environmental factors at the same plots. Our model included hierarchical explanatory variables at both site-level (weather conditions) and plot-level (micro-topographic factors, soil properties, and competing species). The occurrence of Korean fir seedlings was positively associated with moss cover and rock cover but negatively related to dwarf bamboo cover. On site-level, winter precipitation was significantly positively related to the occurrence of seedlings. A hierarchical Poisson regression model revealed that Korean fir density were negatively associated with slope aspect, topographic position index, Quercus mongolica cover, and mean summer temperature. Our results suggest that drought and competition with other species are factors which halt the survival of Korean fir. We can predict that the population of Korean fir will continue to decline on the Korean Peninsula due to rising temperatures and seasonal drought, and only a few Korean fir will survive on northern slopes or valleys where competition with dwarf bamboo and Q. mongolica can be avoided.

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