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Spatial variability of soil nutrients in forest areas: A case study from subtropical China
Author(s) -
Dai Wei,
Li Yuhuan,
Fu Weijun,
Jiang Peikun,
Zhao Keli,
Li Yongfu,
Penttinen Petri
Publication year - 2018
Publication title -
journal of plant nutrition and soil science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.644
H-Index - 87
eISSN - 1522-2624
pISSN - 1436-8730
DOI - 10.1002/jpln.201800134
Subject(s) - topsoil , subtropics , soil carbon , environmental science , geostatistics , soil ph , soil fertility , nutrient , phosphorus , soil test , spatial variability , soil water , soil science , agronomy , ecology , chemistry , mathematics , biology , statistics , organic chemistry
Soil nitrogen (N), phosphorus (P), potassium (K), and pH are important determinants and indicators of soil fertility and quality. Especially in forest, these soil properties are highly variable in space and time. However, more information on these properties in subtropical forests is needed to improve soil nutrients management and to sustain the productivity of subtropical forests. We collected a total of 838 forest topsoil samples (0–30 cm in depth) based on a 4‐km (E‐W) × 6‐km (S‐N) grid system in subtropical China. Geostatistics ( i.e ., global and local Moran's I) and geographical information system (GIS) techniques were applied to reveal the spatial distribution of N, P, and K contents and pH in subtropical forest soils. All the measured properties were highly variable. Soil N contents ranged from 9.55 mg kg −1 to 862.40 mg kg −1 , P contents from 0.10 mg kg −1 to 195.40 mg kg −1 , K contents from 10.00 mg kg −1 to 390.00 mg kg −1 , and pH values from 2.69 to 8.09. The soil N, P and K contents correlated positively with soil organic carbon (SOC), while soil pH correlated negatively with SOC ( P < 0.05). Global Moran's I revealed that soil N, P, and K contents and pH had significant positive spatial autocorrelations, and clear spatial patterns were identified based on local Moran's I. An exponential model was the best fitted model for soil N, P, K contents and pH. Spatial dependence was moderate for all studied soil variables, indicating that both intrinsic and extrinsic factors played a vital role in spatial heterogeneity. Distribution maps showed that soil N and K had similar spatial distribution patterns: a low value area surrounded by bands of higher values. A large‐scale low content area was observed in the spatial distribution map of soil P. An opposite trend was found for the spatial pattern of soil pH. The spatial distribution maps provide useful information for sustainable forest and environment management in subtropical China.