Field-specific simulations of net N mineralization based on digitally available soil and weather data: II. Pedotransfer functions for the pool sizes

Abstract

Avoiding surplus N fertilization without reducing crop yields could be accomplished by accounting for current net N mineralization in N fertilizer recommendations. N simulation models would allow a quantitative consideration of important factors and could be based upon digitally mapped data. Soil-specific temperature and water functions that were derived in part I of the paper needed a differentiation between only three soil groups and the two allocating criteria were taken from digital soil maps. Here, the objectives were to experimentally determine pedotransfer functions (PTFs) for the pool sizes of two organic N pools (N fast , N slow ) that could be calculated via digitally available data and need a minimum set of easily accessible management data. Interestingly, most important input data for the PTFs of both pool sizes were mean clay contents of the texture class (German soil classification system). However, the underlying mechanisms might be different, as N slow could be positively influenced by clay-associated mineralizable SOM, whereas N fast could be positively related to clay content due to higher yield potential and thus more residues on finertextured soils. For N slow including the humus class improved the accuracy of the PTF (r 2 = 0.60; P \ 0.050). For N fast it was important to include a negative influence of the mean fall temperature of the preceding year (r 2 = 0.42; P \ 0.010), probably due to its influence on residue degradation before winter. Surprisingly, easily accessible management data, e.g. previous crop, did not improve the predictions in this study. Field studies with plant cover will have to further prove the applicability of the derived PTFs.

Long-term net N mineralization potential as an indicator for soil fertility: chances and constraints

“…A requirement for these simulations is that specific functions, e.g. pedotransfer functions for the pool sizes of mineralizable soil organic N, are derived by only using data from digital soil maps instead of measured data (Heumann et al 2011a(Heumann et al , 2011b.…”

Depth distribution of mineralizable nitrogen pools in contrasting soils in a semi-arid climate

“…Similarly, Heumann et al (2003) found that the size of the N slow pool of a two-pool first-order kinetic equation can be accurately derived from one or two basic soil characteristics when the sites are grouped by former land-use. Heumann et al (2011) successfully derived pedotransfer functions for predicting the N slow and N fast pool sizes from a two-pool first-order kinetic model using either digitally available or measured soil characteristics. The results of this present study indicate that the depth distribution of soil mineralizable N pools can vary substantially among sites under the semi-arid environment in western Canada.…”

“…However, the depth considered in kinetic models used to predict net N mineralization varies widely. For example, Stanford et al (1977) considered a depth of 0-45 cm; Marion et al (1981) considered depths ranging from 0-13 cm to 0-44 cm, depending on the soil and horizon used; Griffin and Laine (1983) considered the depth of the Ap horizon, which varied with the soil; Cabrera and Kissel (1988) considered a depth of 120 cm, with 15 and 30 cm depth increments; Mikha et al (2006) assumed that the 0-5 cm depth mineralizable N was representative of the 0-30 cm depth considered in their model; and Heumann et al (2002Heumann et al ( , 2011 considered a depth of 28-30 cm. DessureaultRompré et al (2011DessureaultRompré et al ( , 2012) used a kinetic model to predict field-measured soil N supply, and obtained better prediction when using a soil depth of 0-20 or 0-30 cm than when using 0-15 cm.…”

Predicting soil nitrogen supply from soil properties

“…Although we are not aware of previous attempts to predict the mineralizable N parameters of a model such as the zero-plus first-order model, others have attempted to predict the mineralizable N parameters of the two pool model where both pools have first-order kinetics. Heumann et al (2011) derived pedotransfer functions for predicting N slow and N fast pool sizes from a two-pool two-first-order kinetic model using either digitally available or measured soil characteristics. The study included 179 arable soils from Lower Saxony in northwestern Germany with a broad range of soil properties.…”

“…Similarly, Heumann et al (2003) found the size of the N slow pool of a two-pool first-order kinetic equation can be accurately derived from one or two basic soil characteristics when the sites are grouped by former land-use. More recently, Heumann et al (2011) successfully derived pedotransfer functions for predicting the N slow and N fast pool sizes from a two-pool two-first-order kinetic model using either digitally available or measured soil characteristics. The first objective of this study was to develop regression equations to predict the mineralizable N parameters obtained from fitting first-order (i.e., Eq.…”