Appraisal of the Snap Model for Predicting Nitrogen Mineralization in Tropical Soils Under Eucalyptus

Abstract

the soil Nitrogen Availability predictor (sNAp) model predicts daily and annual rates of net N mineralization (NNm) based on daily weather measurements, daily predictions of soil water and soil temperature, and on temperature and moisture modifiers obtained during aerobic incubation (basal rate). the model was based on in situ measurements of NNm in Australian soils under temperate climate. the purpose of this study was to assess this model for use in tropical soils under eucalyptus plantations in São Paulo State, Brazil. Based on field incubations for one month in three, NNm rates were measured at 11 sites (0-20 cm layer) for 21 months. the basal rate was determined in in situ incubations during moist and warm periods (January to march). Annual rates of 150-350 kg ha -1 yr -1 NNm predicted by the sNAp model were reasonably accurate (r 2 = 0.84). in other periods, at lower moisture and temperature, NNm rates were overestimated. therefore, if used carefully, the model can provide adequate predictions of annual NNm and may be useful in practical applications. for NNm predictions for shorter periods than a year or under suboptimal incubation conditions, the temperature and moisture modifiers need to be recalibrated for tropical conditions.

Modeling rhizosphere carbon and nitrogen cycling in <i>Eucalyptus</i> plantation soil

“…The volume of rhizosphere soil is determined by root length and rhizosphere thickness (Finzi et al, 2015). As root length here was based on field measurements (Mello et al, 1998;Neves, 2000;Leles et al, 2001;Teixeira et al, 2002;Gatto et al, 2003;Maquere, 2008), greater remaining uncertainty about the volume of the rhizosphere would be related to its thickness. This, in turn, depends on the amount and nature of rhizosphere deposits and on the physical, chemical, and biological properties of the soil that limit the distribution of those deposits beyond the root surface (Finzi et al, 2015).…”

“…In the logic of ForPRAN, rhizo- sphere volume is related to the length of fine roots and their diameter and also to the thickness of the rhizosphere. Root length is strongly related to shoot biomass as the source of stored and newly fixed C (Mello et al, 1998;Neves, 2000;Leles et al, 2001;Teixeira et al, 2002;Gatto et al, 2003;Maquere, 2008). Root length is also related to soil clay concentration in association with its effects on available water and nutrients.…”

“…Root biomass and depth are estimated in 3-PG but not root length density of fine roots. To represent the growth of fine roots (including root length density), we used a nonlinear model fitted to the data of Mello et al (1998), Neves (2000), Leles et al (2001), Teixeira et al (2002), Gatto et al (2003), and Maquere (2008). Then the rate of C and N release processes from roots are calculated according to Personeni et al (2007) and Farrar et al (2003).…”

“…Most of the parameters present in ForPRAN were based on values observed in previous studies. For instance, parameters used for modeling fine-root growth and rhizodeposition were based on several studies: Mello et al (1998), Neves (2000), Leles et al (2001), Teixeira et al (2002), Gatto et al (2003), Maquere (2008), and Personeni et al (2007). Other parameters used for simulating C and N cycling in rhizosphere soil were based mainly on the studies of Schimel and Wein-traub (2003), Allison et al (2010), and Drake et al (2013).…”

“…. (2001)Teixeira et al (2002) Mello et al (1998 Regression of fine-root biomass reported in the literature against values predicted using the ForPRAN model. The dotted line is the mean regression, with neither intercept nor slope significantly different from 0 or 1, respectively.…”