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Land cover change has been shown to affect soil characteristics and soil organic carbon (SOC) storage. However, little is known about the driving factors associated with soil carbon (C) stabilisation in complex landscapes. This study was conducted to investigate the effects of both inherent soil characteristics and recent vegetation cover change on soil aggregation and soil fraction associated C in a complex landscape. The specific objectives were: (1) determine bulk soil properties and SOC saturation deficit; (2) quantify soil aggregation, soil size-density fractions, and soil fraction associated C; and (3) identify the factors that influence soil fractions and soil fraction associated C in two adjacent catchments differing in vegetation cover, Central Otago, New Zealand. Catchment GH1 (n = 17 plots) was dominated by tussock grassland and native shrubs. Catchment GH2 (n = 21 plots) was converted from tussock grassland into a pine forest in 1981. The catchments differed in soil texture (e.g. sand content GH1: 62.9%, GH2: 50.7%, P = 0.007), soil SOC stocks (GH1: 5.0 kg C [m.sup.-2], GH2: 4.3 kg C [m.sup.-2], P = 0.04), mean weight diameter (MWD) (GH1: 782.3 [micro]m, GH2: 736.5 [micro]m, P = 0.002), and proportion of the macroaggregate heavy fraction (macro_HF) (GH1: 72%, GH2: 55%, P = 0.01). No significant differences were found in SOC saturation deficit (GH1: 14.8 mg [g.sup.-1], GH2: 13.1 mg [g.sup.-1], P = 0.13). Dominant vegetation cover explained 21% of the variation in MWD in GH1, whereas silt+clay C content explained 31.6% of the MWD variation in GH2. The macro_HF fraction was negatively correlated with the proportion of silt+clay. Our findings illustrate that physical and chemical soil characteristics are important drivers in such a complex landscape and may have masked the effect of recent vegetation change on soil aggregation, and soil fraction associated C. Additional keywords: land cover change, New Zealand, pine forest, shrub encroachment, size-density fractionation, soil aggregation, soil organic carbon saturation. Received 9 July 2018, accepted 1 February 2019, published online 7 March 2019, Introduction Soil is the largest terrestrial carbon (C) pool, storing four times more C than the biosphere and over three times more C than the atmosphere (Lai 2008; Stockmann et [...]

Despite the importance of soil physical properties on water infiltration and redistribution, little is known about the effect of variability in soil properties and its consequent effect on contaminant loss pathways. To investigate the effects of uncertainty and heterogeneity in measured soil physical parameters on the simulated movement of water and the prediction of nitrous oxide ([N.sub.2]O) emissions, we set up the Agricultural Production Systems sIMulator (APSIM) for different soil types in three different regions of New Zealand: the Te Kowhai silt loam and the Horotiu silt loam in the Waikato region, and the Templeton silt loam in the Canterbury region, and the Otokia silt loam and the Wingatui silt loam in the Otago region. For each of the soil types, various measured soil profile descriptions, as well as those from a national soils database (S-map) were used when available. In addition, three different soil water models in APSIM with different complexities (SWIM2, SWIM3, and SoilWat) were evaluated. Model outputs were compared with temporal soil water content measurements within the top 75 mm at the various experimental sites. Results show that the profile description, as well as the soil water model used affected the prediction accuracy of soil water content. The smallest difference between soil profile descriptions was found for the Templeton soil series, where the model efficiency (NSE) was positive for all soil profile descriptions, and the RMSE ranged from 0.055 to 0.069 [m.sup.3]/[m.sup.3]. The greatest difference was found for the Te Kowhai soil, where only one of the descriptions showed a positive NSE, and the other two profile descriptions overestimated measured topsoil water contents. Furthermore, it was shown that the soil profile description highly affects [N.sub.2]O emissions from urinary N deposited during animal grazing. However, the relative difference between the emissions was not always related to the accuracy of the measured soil water content, with soil organic carbon content also affecting emissions.Additional keywords: APSIM modelling, [N.sub.2]O emissions, soil water content, soil water module complexity.Received 23 March 2018, accepted 4 September 2018, published online 11 October 2018, IntroductionLand management models are increasingly being used to inform government policy that addresses challenges such as farming within environmental limits, and climate change mitigation and adaptation (Holzworth et al. 2017). [...]

The emission of nitrous oxide (N2O) from agricultural soils to the atmosphere is a significant contributor to anthropogenic greenhouse gas emissions. The recycling of organic nitrogen (N) in manure and crop residues may result in spatiotemporal variability of N2O production and soil efflux which is difficult to capture by process-based models. We propose a multi-species, reactive transport model to provide detailed insight into the spatiotemporal variability of nitrogen (N) transformations around such N2O hotspots, which consists of kinetic reactions of soil respiration, nitrification, nitrifier denitrification, and denitrification represented by a system of coupled partial differential equations. The model was tested with results from an incubation experiment at two different soil moisture levels (-30 and -100 hPa, respectively) and was shown to reasonably well reproduce the recorded N2O and dinitrogen (N2) emissions, and the dynamics of important carbon (C) and N components in soil. The simulation indicated that the four populations developed in closely connected, but separate layers, with denitrifying bacteria growing within the manure-dominated zone and nitrifying bacteria in the well-aerated soil outside the manure zone and with time also within the manure layer. The modeled N2O production within the manure zone was greatly enhanced by the combined effect of oxygen deficit, abundant carbon source and supply of nitrogenous substrates. In the wetter soil treatment with a water potential of -30 hPa, diffusive flux of nitrate (NO3-) across the manure-soil interface was the main source of NO3- for denitrification in the manure zone, while at a soil water potential of -100 hPa, diffusion became less dominant and overtaken by the co-occurrence of nitrification and denitrification in the manure zone. Scenarios were analyzed where diffusive transport of dissolved organic carbon or different mineral N species were switched off, and they showed that the simultaneous diffusion of NO3-, ammonium (NH4+), and nitrite (NO2-) were crucial to simulate the dynamics of N transformations and N2O emissions in the model. Without considering solute diffusion in process-based N2O models, the rapid turnover of C and N associated with organic hotspots can not be accounted for, and it may result in underestimation of N2O emissions from soil after manure application. The model and its parameters allow for new detailed insights into the interactions between transport and microbial transformations associated with N2O emissions in heterogeneous soil environments. [ABSTRACT FROM AUTHOR]

Investigation of land-use and management changes at regional scales require the linkage of farm-system models with land-resource information, which for pastoral systems includes forage supply. The New Zealand Land Resource Inventory (NZLRI) and associated Land Use Capability (LUC) database include estimates of the potential stock-carrying capacity across the country, which can be used to derive estimates of average annual pasture yields. Farm system models and decision support tools, however, require information on the seasonal patterns of pasture growth. To generate such pasture growth curves (PGCs), the Agricultural Production Systems Simulator (APSIM) was used, with generic soil profiles based on descriptions of LUC classes, to generate PGCs for three regions of New Zealand. Simulated annual pasture yields were similar to the estimates of annual potential pasture yield in the NZLRI spatial database, and they provided information on inter-annual variability. Simulated PGCs generally agreed well with measured long-term patterns of seasonal pasture growth. The approach can be used to obtain spatially discrete estimates of seasonal pasture growth patterns across New Zealand for use in farm system models and for assessing the impact of management practices and climate change on the regional sustainability. Additional keywords: cluster analysis, LUC soil profile descriptions, pasture growths curve., Introduction Pastoral agriculture is the major land use in New Zealand, covering -40% of the total land area. Of this land, -55% comprises improved pastures in flat to rolling terrain [...]