4.7 Article

Within-site drivers for soil nutrient variability in plantation forests: A case study from dry sub-humid New Zealand

期刊

CATENA
卷 200, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.catena.2021.105149

关键词

Soil chemical properties; Spatial variability; Sub-humid environment; Plantation forest; Generalised Linear Mixed-effect Model (GLMM); Topographic variables

资金

  1. Specialty Wood Product (SWP) Partnership of the New Zealand Ministry of Business, Innovation and Employment (MBIE)

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Spatial variability of soil properties in plantation forests is significant, with factors such as slope, aspect, and topography playing a key role. Understanding these variations can improve soil nutrient management and sustainability in forest productivity. The study found correlations between soil properties and topographic features, such as morphometric protection index and wind exposition index, highlighting the importance of shelter from relief and wind on soil characteristics.
Precise spatial information on soil properties in plantation forests is needed to improve soil nutrient management and to sustain productivity. Soil nitrogen, phosphorus, potassium, organic matter, carbon and boron are important determinants and indicators of soil fertility and quality. Particularly in forests, these soil properties are highly variable in space and time. In this study, soils were sampled from three plantation forest sites in a dry sub-humid region near Blenheim, New Zealand. Thirty sampling points were selected, and samples were collected from the three sites across a range of slope and aspect strata. Soil samples were analysed for total carbon (totC), total nitrogen (totN), total phosphorus (totP), extractable potassium (exK) and hot-water extractable boron (exB). All examined soil properties varied significantly (p < 0.05) within sites. A set of fine-scale (5 m resolution) topographic surfaces, that might explain this variability, were then interpolated or derived in geographic information system software. Topographic surfaces included elevation, aspect, slope, profile and plan curvature, topographic position index (TPI), topographic wetness index (TWI), wind exposition index (WEI), and morphometric protection index (MPI). A generalised linear mixed-effect model was applied to develop predictive models. The study found all soil properties were positively correlated with MPI and negatively correlated with the WEI. This indicated that soil properties were correlated with shelter from surrounding relief and wind. Interestingly, within-site boron levels were correlated with both profile curvature (PrCurv) and topographic wetness index, indicating boron movement through the surface with the movement of soil moisture. The modelling approach in this study has potential for application to sustainable management of plantation forests using spatially-precise estimates of soil fertility.

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