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Advancing analysis of spatio-temporal variations of soil nutrients in the water level fluctuation zone of China's Three Gorges Reservoir using self-organizing map.

Ye C, Li S, Yang Y, Shu X, Zhang J, Zhang Q - PLoS ONE (2015)

Bottom Line: Results showed significant spatial variability in nutrients along ~600 km long shoreline of the TGR before and after submergence.Submergence enhanced soil available potassium (K), while significantly decreased soil N, possibly due to the alterations of soil particle size composition and increase in soil pH.Our results suggest that urban sewage and agricultural runoffs are primary pollutants that affect soil nutrients in the WLFZ of TGR.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, China.

ABSTRACT
The ~350 km2 water level fluctuation zone (WLFZ) in the Three Gorges Reservoir (TGR) of China, situated at the intersection of terrestrial and aquatic ecosystems, experiences a great hydrological change with prolonged winter inundation. Soil samples were collected in 12 sites pre- (September 2008) and post submergence (June 2009) in the WLFZ and analyzed for soil nutrients. Self-organizing map (SOM) and statistical analysis including multi-way ANOVA, paired-T test, and stepwise least squares multiple regression were employed to determine the spatio-temporal variations of soil nutrients in relation to submergence, and their correlations with soil physical characteristics. Results showed significant spatial variability in nutrients along ~600 km long shoreline of the TGR before and after submergence. There were higher contents of organic matter, total nitrogen (TN), and nitrate (NO3-) in the lower reach and total phosphorus (TP) in the upper reach that were primarily due to the spatial variations in soil particle size composition and anthropogenic activities. Submergence enhanced soil available potassium (K), while significantly decreased soil N, possibly due to the alterations of soil particle size composition and increase in soil pH. In addition, SOM analysis determined important roles of soil pH value, bulk density, soil particle size (i.e., silt and sand) and nutrients (TP, TK, and AK) on the spatial and temporal variations in soil quality. Our results suggest that urban sewage and agricultural runoffs are primary pollutants that affect soil nutrients in the WLFZ of TGR.

No MeSH data available.


Related in: MedlinePlus

Spatial difference of soil quality parameters before submergence: (A) hit histogram (i.e., data density indicated by the circle size) in a U-matrix illustrating the differences among sampling sites (upper-red circles, middle-yellow circles, and lower-green circles), (B) hit histogram indicating variations among three elevation intervals (145–155 m-red circles, 155–165 m-yellow circles, and 165–175 m-green circles), and (C) rank of significant parameters from the highest rank in the top to the lowest in the bottom.A larger circle denotes a higher density of the data in the hexagonal grid unit, and the grayscale is the U-matrix representing the Euclidean distance between the neighboring map units (i.e., grayscale located at the intermediate position between the units). Light regions imply a high degree of similarity between the units, whereas dark areas represent a large distance. Percentage statistics (means and standard error) for the rank are averaged based on the first four SOM units with larger Euclidean distance among data vectors (Ki et al., 2011).
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pone.0121210.g006: Spatial difference of soil quality parameters before submergence: (A) hit histogram (i.e., data density indicated by the circle size) in a U-matrix illustrating the differences among sampling sites (upper-red circles, middle-yellow circles, and lower-green circles), (B) hit histogram indicating variations among three elevation intervals (145–155 m-red circles, 155–165 m-yellow circles, and 165–175 m-green circles), and (C) rank of significant parameters from the highest rank in the top to the lowest in the bottom.A larger circle denotes a higher density of the data in the hexagonal grid unit, and the grayscale is the U-matrix representing the Euclidean distance between the neighboring map units (i.e., grayscale located at the intermediate position between the units). Light regions imply a high degree of similarity between the units, whereas dark areas represent a large distance. Percentage statistics (means and standard error) for the rank are averaged based on the first four SOM units with larger Euclidean distance among data vectors (Ki et al., 2011).

Mentions: Figs. 6 and 7 illustrated the spatial variabilities of soil quality among the upper (red circles), middle (yellow circles) and lower reaches (green circles) in the WLFZ and their dominant influencing factors. Before submergence, the samples corresponding to the upper and lower reaches were concentrated in a more compact region in the map than those in the middle reach (Fig. 6A). Samples belonging to each elevation interval were evenly distributed (Fig. 6B). The pH and bulk density had significant effects on the boundaries constructed, and TP and TK had relatively more important effects on soil quality compared to other soil nutrients (Fig. 6C). After the submergence, samples belonging to each cluster were evenly distributed across the SOM map (Fig. 7A), while samples in the elevation of 145–155 m were concentrated in a more compact region than samples in other elevations (Fig. 7B). The pH and silt showed significant effects on the boundaries and were associated with TK and TP, while AP, OM, NH4+ and TN had lower impacts on the borders (Fig. 7C). Fig. 8 depicted the temporal variability of soil quality before submergence (red circles) and after submergence (green circles) in the WLFZ. The pH and sand were associated with TP and AK, and played an important role in the boundaries, whereas negligible or smaller effects were observed for TN, AP, clay and NH4+.


Advancing analysis of spatio-temporal variations of soil nutrients in the water level fluctuation zone of China's Three Gorges Reservoir using self-organizing map.

Ye C, Li S, Yang Y, Shu X, Zhang J, Zhang Q - PLoS ONE (2015)

Spatial difference of soil quality parameters before submergence: (A) hit histogram (i.e., data density indicated by the circle size) in a U-matrix illustrating the differences among sampling sites (upper-red circles, middle-yellow circles, and lower-green circles), (B) hit histogram indicating variations among three elevation intervals (145–155 m-red circles, 155–165 m-yellow circles, and 165–175 m-green circles), and (C) rank of significant parameters from the highest rank in the top to the lowest in the bottom.A larger circle denotes a higher density of the data in the hexagonal grid unit, and the grayscale is the U-matrix representing the Euclidean distance between the neighboring map units (i.e., grayscale located at the intermediate position between the units). Light regions imply a high degree of similarity between the units, whereas dark areas represent a large distance. Percentage statistics (means and standard error) for the rank are averaged based on the first four SOM units with larger Euclidean distance among data vectors (Ki et al., 2011).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4366114&req=5

pone.0121210.g006: Spatial difference of soil quality parameters before submergence: (A) hit histogram (i.e., data density indicated by the circle size) in a U-matrix illustrating the differences among sampling sites (upper-red circles, middle-yellow circles, and lower-green circles), (B) hit histogram indicating variations among three elevation intervals (145–155 m-red circles, 155–165 m-yellow circles, and 165–175 m-green circles), and (C) rank of significant parameters from the highest rank in the top to the lowest in the bottom.A larger circle denotes a higher density of the data in the hexagonal grid unit, and the grayscale is the U-matrix representing the Euclidean distance between the neighboring map units (i.e., grayscale located at the intermediate position between the units). Light regions imply a high degree of similarity between the units, whereas dark areas represent a large distance. Percentage statistics (means and standard error) for the rank are averaged based on the first four SOM units with larger Euclidean distance among data vectors (Ki et al., 2011).
Mentions: Figs. 6 and 7 illustrated the spatial variabilities of soil quality among the upper (red circles), middle (yellow circles) and lower reaches (green circles) in the WLFZ and their dominant influencing factors. Before submergence, the samples corresponding to the upper and lower reaches were concentrated in a more compact region in the map than those in the middle reach (Fig. 6A). Samples belonging to each elevation interval were evenly distributed (Fig. 6B). The pH and bulk density had significant effects on the boundaries constructed, and TP and TK had relatively more important effects on soil quality compared to other soil nutrients (Fig. 6C). After the submergence, samples belonging to each cluster were evenly distributed across the SOM map (Fig. 7A), while samples in the elevation of 145–155 m were concentrated in a more compact region than samples in other elevations (Fig. 7B). The pH and silt showed significant effects on the boundaries and were associated with TK and TP, while AP, OM, NH4+ and TN had lower impacts on the borders (Fig. 7C). Fig. 8 depicted the temporal variability of soil quality before submergence (red circles) and after submergence (green circles) in the WLFZ. The pH and sand were associated with TP and AK, and played an important role in the boundaries, whereas negligible or smaller effects were observed for TN, AP, clay and NH4+.

Bottom Line: Results showed significant spatial variability in nutrients along ~600 km long shoreline of the TGR before and after submergence.Submergence enhanced soil available potassium (K), while significantly decreased soil N, possibly due to the alterations of soil particle size composition and increase in soil pH.Our results suggest that urban sewage and agricultural runoffs are primary pollutants that affect soil nutrients in the WLFZ of TGR.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, China.

ABSTRACT
The ~350 km2 water level fluctuation zone (WLFZ) in the Three Gorges Reservoir (TGR) of China, situated at the intersection of terrestrial and aquatic ecosystems, experiences a great hydrological change with prolonged winter inundation. Soil samples were collected in 12 sites pre- (September 2008) and post submergence (June 2009) in the WLFZ and analyzed for soil nutrients. Self-organizing map (SOM) and statistical analysis including multi-way ANOVA, paired-T test, and stepwise least squares multiple regression were employed to determine the spatio-temporal variations of soil nutrients in relation to submergence, and their correlations with soil physical characteristics. Results showed significant spatial variability in nutrients along ~600 km long shoreline of the TGR before and after submergence. There were higher contents of organic matter, total nitrogen (TN), and nitrate (NO3-) in the lower reach and total phosphorus (TP) in the upper reach that were primarily due to the spatial variations in soil particle size composition and anthropogenic activities. Submergence enhanced soil available potassium (K), while significantly decreased soil N, possibly due to the alterations of soil particle size composition and increase in soil pH. In addition, SOM analysis determined important roles of soil pH value, bulk density, soil particle size (i.e., silt and sand) and nutrients (TP, TK, and AK) on the spatial and temporal variations in soil quality. Our results suggest that urban sewage and agricultural runoffs are primary pollutants that affect soil nutrients in the WLFZ of TGR.

No MeSH data available.


Related in: MedlinePlus