Recovery of herb‐layer vegetation and soil properties after pile burning in a Midwestern oak woodland

2021 ◽  
Author(s):  
Matthew A. Albrecht ◽  
Noah D. Dell ◽  
Megan J. Engelhardt ◽  
J. Leighton Reid ◽  
Michael L. Saxton ◽  
...  
Keyword(s):  
Soil Properties ◽  
Herb Layer ◽  
Oak Woodland

Little evidence of native and non-native species influencing one another's abundance and distribution in the herb layer of an oak woodland

2015 ◽  
Vol 26 (5) ◽  
pp. 1005-1012 ◽  
Author(s):  
Mark A. Davis ◽  
Michael D. Anderson ◽  
Lilly Bock-Brownstein ◽  
Anna Staudenmaier ◽  
Melena Suliteanu ◽  
...  
Keyword(s):  
Native Species ◽  
Herb Layer ◽  
Oak Woodland ◽  
Abundance And Distribution

scholarly journals Variation in floristic and trait composition along environmental gradients in the herb layer of temperate forests in the transition zone between Central and SE Europe

Plant Ecology ◽  
2021 ◽  
Author(s):  
Janez Kermavnar ◽  
Lado Kutnar ◽  
Aleksander Marinšek
Keyword(s):  
Species Composition ◽  
Soil Properties ◽  
Tree Species ◽  
Floristic Composition ◽  
Soil Conditions ◽  
Mean Annual Temperature ◽  
Herb Layer ◽  
Climatic Parameters ◽  
Tree Layer ◽  
Plant Growth Habit

AbstractSpecies- and trait-environment linkages in forest plant communities continue to be a frequent topic in ecological research. We studied the dependence of floristic and functional trait composition on environmental factors, namely local soil properties, overstory characteristics, climatic parameters and other abiotic and biotic variables. The study area comprised 50 monitoring plots across Slovenia, belonging to the EU ICP Forests monitoring network. Vegetation was surveyed in accordance with harmonized protocols, and environmental variables were either measured or estimated during vegetation sampling. Significant predictors of species composition were identified by canonical correspondence analysis. Correlations between plant traits, i.e. plant growth habit, life form, flowering features and CSR signature, were examined with fourth-corner analysis and linear regressions. Our results show that variation in floristic composition was mainly explained by climatic parameters (mean annual temperature, mean annual precipitation), soil properties (pH) and tree layer-dependent light conditions. Trait composition was most closely related with tree layer characteristics, such as shade-casting ability (SCA, a proxy for light availability in the understory layer), tree species richness and tree species composition. Amongst soil properties, total nitrogen content and soil texture (proportion of clay) were most frequently correlated with different species traits or trait states. The CSR signature of herb communities was associated with tree layer SCA, soil pH and mean annual temperature. The floristic composition of the studied herb-layer vegetation depended on temperature and precipitation, which are likely to be influenced by ongoing climate change (warming and drying). Trait composition exhibited significant links to tree layer characteristics and soil conditions, which are in turn directly modified by forest management interventions.

Applying the Method of Lagrange Multipliers to Derive an Estimator for Unsampled Soil Properties

2014 ◽  
Vol 11 (1) ◽  
pp. 15
Author(s):  
Set Foong Ng ◽  
Pei Eng Ch’ng ◽  
Yee Ming Chew ◽  
Kok Shien Ng
Keyword(s):  
Soil Properties ◽  
Lagrange Multipliers ◽  
Unbiased Estimator ◽  
Soil Property ◽  
Minimum Variance ◽  
Distance Method ◽  
True Value ◽  
A Site ◽  
Method Of Lagrange Multipliers ◽  
Inverse Distance

Soil properties are very crucial for civil engineers to differentiate one type of soil from another and to predict its mechanical behavior. However, it is not practical to measure soil properties at all the locations at a site. In this paper, an estimator is derived to estimate the unknown values for soil properties from locations where soil samples were not collected. The estimator is obtained by combining the concept of the ‘Inverse Distance Method’ into the technique of ‘Kriging’. The method of Lagrange Multipliers is applied in this paper. It is shown that the estimator derived in this paper is an unbiased estimator. The partiality of the estimator with respect to the true value is zero. Hence, the estimated value will be equal to the true value of the soil property. It is also shown that the variance between the estimator and the soil property is minimised. Hence, the distribution of this unbiased estimator with minimum variance spreads the least from the true value. With this characteristic of minimum variance unbiased estimator, a high accuracy estimation of soil property could be obtained.

AVAILABLE WAYS TO OPTIMIZE SOIL PROPERTIES IN APPLE ORCHARDS

2020 ◽  
Vol 16 (2) ◽  
pp. 41-63
Author(s):  
V.L. Zakharov ◽  
◽  
G.N. Pugachev ◽  
Keyword(s):  
Soil Properties ◽  
Apple Orchards
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