Spatial nutrients that includes OM, Avail.K, Avail.P and TN distribution and the influences on vegetation patterns in Dalingshan was the cardinal focus of this study. Ecological data (moisture content, bulk density and topography) were considered. One way ANOVA was statistically tested of spatial distribution of major nutrients across 4 plots which indicated non significant at p = 0.05 level, TN (p = 0.0216), OM (p = 0.00004), Avail.K (p = 0.00216) respectively. Furthermore one way ANOVA was tested on acidity level (pH) measured against the nutrients distribution TN (p = 0.0031), OM (p = 0.0004), Avail.K (p = 0.0216) respectively at non significance level but available phosphorous was significantly different (p = 0.6412). The study revealed unique spatial patterns of soil nutrient distribution in Dalingshan and species abundance while vegetation census posed a new direction of study that may be adapted for a broad range of regional vegetation and floristic modeling. This paper suggests that forest soil nutrients and vegetation interaction can be utilized for further studies on multifactor ecosystem responses towards regional ecological restoration.
| DOI | 10.11648/j.aff.s.2015040301.11 |
| Published in |
Agriculture, Forestry and Fisheries (Volume 4, Issue 3-1, May 2015)
This article belongs to the Special Issue Environment and Applied Science Management in a Changing Global Climate |
| Page(s) | 1-4 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Spatial Patterns, Soil Nutrient, Vegetation Cover, TWINSPAN, Dalingshan Guangdong Province China
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APA Style
Egbuche C. T., Su Zhiyoa, Anyanwu J. C., Onweremadu E. U., Nwaihu E. C., et al. (2015). Spatial Patterns of Nutrient Distribution in Dalingshan Forest Soil of Guangdong Province China. Agriculture, Forestry and Fisheries, 4(3-1), 1-4. https://doi.org/10.11648/j.aff.s.2015040301.11
ACS Style
Egbuche C. T.; Su Zhiyoa; Anyanwu J. C.; Onweremadu E. U.; Nwaihu E. C., et al. Spatial Patterns of Nutrient Distribution in Dalingshan Forest Soil of Guangdong Province China. Agric. For. Fish. 2015, 4(3-1), 1-4. doi: 10.11648/j.aff.s.2015040301.11
AMA Style
Egbuche C. T., Su Zhiyoa, Anyanwu J. C., Onweremadu E. U., Nwaihu E. C., et al. Spatial Patterns of Nutrient Distribution in Dalingshan Forest Soil of Guangdong Province China. Agric For Fish. 2015;4(3-1):1-4. doi: 10.11648/j.aff.s.2015040301.11
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Download@article{10.11648/j.aff.s.2015040301.11,
author = {Egbuche C. T. and Su Zhiyoa and Anyanwu J. C. and Onweremadu E. U. and Nwaihu E. C. and Umeojiakor A. O. and A. E. Ibe},
title = {Spatial Patterns of Nutrient Distribution in Dalingshan Forest Soil of Guangdong Province China},
journal = {Agriculture, Forestry and Fisheries},
volume = {4},
number = {3-1},
pages = {1-4},
doi = {10.11648/j.aff.s.2015040301.11},
url = {https://doi.org/10.11648/j.aff.s.2015040301.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aff.s.2015040301.11},
abstract = {Spatial nutrients that includes OM, Avail.K, Avail.P and TN distribution and the influences on vegetation patterns in Dalingshan was the cardinal focus of this study. Ecological data (moisture content, bulk density and topography) were considered. One way ANOVA was statistically tested of spatial distribution of major nutrients across 4 plots which indicated non significant at p = 0.05 level, TN (p = 0.0216), OM (p = 0.00004), Avail.K (p = 0.00216) respectively. Furthermore one way ANOVA was tested on acidity level (pH) measured against the nutrients distribution TN (p = 0.0031), OM (p = 0.0004), Avail.K (p = 0.0216) respectively at non significance level but available phosphorous was significantly different (p = 0.6412). The study revealed unique spatial patterns of soil nutrient distribution in Dalingshan and species abundance while vegetation census posed a new direction of study that may be adapted for a broad range of regional vegetation and floristic modeling. This paper suggests that forest soil nutrients and vegetation interaction can be utilized for further studies on multifactor ecosystem responses towards regional ecological restoration.},
year = {2015}
}
TY - JOUR T1 - Spatial Patterns of Nutrient Distribution in Dalingshan Forest Soil of Guangdong Province China AU - Egbuche C. T. AU - Su Zhiyoa AU - Anyanwu J. C. AU - Onweremadu E. U. AU - Nwaihu E. C. AU - Umeojiakor A. O. AU - A. E. Ibe Y1 - 2015/05/19 PY - 2015 N1 - https://doi.org/10.11648/j.aff.s.2015040301.11 DO - 10.11648/j.aff.s.2015040301.11 T2 - Agriculture, Forestry and Fisheries JF - Agriculture, Forestry and Fisheries JO - Agriculture, Forestry and Fisheries SP - 1 EP - 4 PB - Science Publishing Group SN - 2328-5648 UR - https://doi.org/10.11648/j.aff.s.2015040301.11 AB - Spatial nutrients that includes OM, Avail.K, Avail.P and TN distribution and the influences on vegetation patterns in Dalingshan was the cardinal focus of this study. Ecological data (moisture content, bulk density and topography) were considered. One way ANOVA was statistically tested of spatial distribution of major nutrients across 4 plots which indicated non significant at p = 0.05 level, TN (p = 0.0216), OM (p = 0.00004), Avail.K (p = 0.00216) respectively. Furthermore one way ANOVA was tested on acidity level (pH) measured against the nutrients distribution TN (p = 0.0031), OM (p = 0.0004), Avail.K (p = 0.0216) respectively at non significance level but available phosphorous was significantly different (p = 0.6412). The study revealed unique spatial patterns of soil nutrient distribution in Dalingshan and species abundance while vegetation census posed a new direction of study that may be adapted for a broad range of regional vegetation and floristic modeling. This paper suggests that forest soil nutrients and vegetation interaction can be utilized for further studies on multifactor ecosystem responses towards regional ecological restoration. VL - 4 IS - 3-1 ER -
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