Search

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). [...]

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 [...]

Modelling water and solute transport through soil requires the characterisation of the soil hydraulic functions; however, determining these functions based on measurements is time-consuming and costly. Pedotransfer functions (PTFs), which make use of easily measurable soil properties to predict the hydraulic functions, have been proposed as an alternative to measurements. The better known and more widely used PTFs were developed in the USA or Europe, where large datasets exist. No specific PTFs have been published for New Zealand soils. To address this gap, we evaluated a range of published PTFs against an available dataset comprising a range of different soils from New Zealand and selected the best PTFs to construct an ensemble PTF (ePTF). Assessment (and adjustment when required) of published PTFs was done by comparing measurements and estimates of soil water content and the hydraulic conductivity at selected matric suction values. For each point, the best two or three PTFs were chosen to compose the ePTF, with correcting constants if needed. The outputs of the ePTF are the hydraulic properties at selected matric suctions, akin to obtaining measurements, thus allowing the fit of different equations as well as combining any available measurements. Testing of the ePTF showed promising performance, with reasonably accurate estimates of the water retention of an independent dataset. Root mean square error values averaged 0.06 [m.sup.3] [m.sup.-3] for various New Zealand soils, which is within the accuracy level of published PTF studies. The largest errors were found for soils with high clay content, for which the ePTF should be used with care. The performance of the ePTF for estimating soil hydraulic conductivity was not as reliable as for water content, exhibiting large scatter. Predictions of saturated hydraulic conductivity were of the same magnitude as the measurements, whereas the unsaturated values were generally under- predicted. The conductivity data available for this study were limited and highly variable. The estimates for hydraulic conductivity should therefore be used with much care, and future research should address measurements and analysis to improve the predictions. The cPTF was also used to parameterise the SWIM soil module for use in Agricultural Production Systems Simulator (APSIM) simulations. Comparisons of drainage predicted by APSIM against results from lysimeter experiments suggest that the use of the derived ePTF is suited for the estimation of soil parameters for use in modelling. The ePTF is not envisaged as a substitute for measurements but is a useful tool to complement datasets with limited amounts of measured data. Additional keywords: APSIM, drainage, hydraulic conductivity, simulation modelling, soil water content, volcanic soils., Introduction Soil hydraulic characteristics are among the most important properties for characterising physical behaviour of a soil type. Quantitative descriptions of either the characteristic points (water content values at saturation, [...]

Nitrous oxide ([N.sub.2]O) emissions from agriculture are generally estimated using default IPCC emission factors (EFs) despite the large variation in measured EFs. We used a classification and regression tree (CART) analysis to segregate measured EFs from direct emissions from urine patches and fertiliser and effluent applications, based on temporal and site-specific factors. These segregated EFs were linked to simulations from the DairyNZ Whole Farm Model to obtain N20 emissions for a typical pasture-based dairy farm in New Zealand. The [N.sub.2]O emissions from urine patches, dung pads, and fertiliser and effluent application, as well as from indirect sources, were aggregated to obtain total [N.sub.2]O emissions for the farm-scale. The results, based on segregated EFs, were compared with those obtained using New Zealand-specific EFs. On-farm [N.sub.2]O emissions based on these segregated EFs were 5% lower than those based on New Zealand-specific EFs. Improved farm management by avoiding grazing, effluent, and N fertiliser application during periods of high risk for [N.sub.2]O emissions, or by the use of mitigation technologies such as nitrification inhibitors, could reduce annual farm scale [N.sub.2]O emissions. Additional keywords: CART analysis, fertiliser, nitrous oxide emission factors, [N.sub.2]O database NZ, urine. Received 13 March 2011, accepted 13 April 2012, published online 14 May 2012, Introduction Nitrous oxide ([N.sub.2]O) emissions from agricultural soils are a major source of greenhouse gas (GHG) emissions in many countries, including New Zealand. Waste from animal excreta contributes as much [...]

As commented in our paper (Vogeler et al. 2016) and pointed out by Lynn (2017), there is a large demand for production and environmental analyses on medium and large spatial [...]