Effects of nitrogen fertilization and bioenergy crop species on central tendency and spatial heterogeneity of soil glycosidase activities

Abstract

Extracellular glycosidases in soil, produced by microorganisms, act as major agents for decomposing labile soil organic carbon (e.g., cellulose). Soil extracellular glycosidases are significantly affected by nitrogen (N) fertilization but fertilization effects on spatial distributions of soil glycosidases have not been well addressed. Whether the effects of N fertilization vary with bioenergy crop species also remains unclear. Based on a 3-year fertilization experiment in Middle Tennessee, USA, a total of 288 soil samples in topsoil (0-15 cm) were collected from two 15 m² plots under three fertilization treatments in switchgrass (SG: Panicum virgatum L.) and gamagrass (GG: Tripsacum dactyloides L.) using a spatially explicit design. Four glycosidases, α-glucosidase (AG), β-glucosidase (BG), β-xylosidase (BX), cellobiohydrolase (CBH), and their sum associated with C acquisition (C_acq) were quantified. The three fertilization treatments were no N input (NN), low N input (LN: 84 kg N ha^-1 year^-1 in urea) and high N input (HN: 168 kg N ha^-1 year^-1 in urea). The descriptive and geostatistical approaches were used to evaluate their central tendency and spatial heterogeneity. Results showed significant interactive effects of N fertilization and crop type on BX such that LN and HN significantly enhanced BX by 14% and 44% in SG, respectively. The significant effect of crop type was identified and glycosidase activities were 15-39% higher in GG than those in SG except AG. Within-plot variances of glycosidases appeared higher in SG than GG but little differed with N fertilization due to large plot-plot variation. Spatial patterns were generally more evident in LN or HN plots than NN plots for BG in SG and CBH in GG. This study suggested that N fertilization elevated central tendency and spatial heterogeneity of glycosidase activities in surficial soil horizons and these effects however varied with crop and enzyme types. Future studies need to focus on specific enzyme in certain bioenergy cropland soil when N fertilization effect is evaluated.

Figure 1

Illustration of an efficient clustered random sampling design within a plot (2.75 m × 5.5 m). The plot was divided into eight subplots (grey zone) and there was a centroid (dark solid circle) in each subplot (1.375 m × 1.375 m), where three soil sampling points (+) were determined from random directions and distances from a centroid in each sampling region (grey area). The extent of an interpolation map was thus determined by the minimum and maximum values at horizontal and vertical axes, and each map can attain its extent less than or equivalent to a plot area.

Figure 2

Frequency histograms of AG, BG, BX, CBH and C_acq under three N fertilization treatments (NN, LN and HN) in two bioenergy croplands (SG and GG). The number on the x-axis (i.e. 0.45, 0.89 in (a) represents a range of (0.00, 0.45) and (0.45, 0.89), respectively. The abbreviations are referred to Tables 1 and 2.

Figure 3

Within-plot CVs of AG, BG, BX, CBH and C_acq under three N fertilization treatments (NN, LN and HN) in two bioenergy croplands (SG and GG). The dashed lines represent a CV of 20% and 40%. Different lowercase letters denote significant difference in CV between fertilization treatments and different uppercase letters between crop species for each enzyme at P < 0.05. The abbreviations are referred to Tables 1 and 2.

Figure 4

Plots of log transformed sample size requirements (SSR) and desired relative errors AG, BG, BX, CBH and C_acq under three N fertilization treatments (NN, LN and HN) in two bioenergy croplands (SG and GG). NN: red dotted line; LN: black dotted line; and HN: black solid line. The log scale was applied on both axes. The abbreviations are referred to Tables 1 and 2. SSR denotes the average of two plots in each treatment.

Figure 5

Correlograms of Moran’s I for AG under three N fertilization treatments (NN, LN and HN) in two bioenergy croplands (SG and GG). Filled circles, positioned beyond the upper and lower dashed lines, represent positive or negative Moran’s I values that exhibited significant autocorrelation. Obs: observations; LCL: low confident limit; and UCL: upper confident limit. Abbreviations are referred to Tables 1 and 2.

Figure 6

Spatial distributions of AG, BG, BX, CBH and C_acq activity in soils under three N fertilization treatments (i.e. NN, LN and HN) in SG. The interpolation maps were produced by inverse distance weighting (IDW) method using ArcGIS software by Esri (version 10.2.1, http://www.esri.com). The abbreviations are referred to Tables 1 and 2.

Figure 7

Spatial distributions of AG, BG, BX, CBH and C_acq activity in soils under three N fertilization treatments (i.e. NN, LN and HN) in GG. The interpolation maps were produced by inverse distance weighting (IDW) method using ArcGIS software by Esri (version 10.2.1, http://www.esri.com). The abbreviations are referred to Tables 1 and 2.