GrassGroTM simulation of pasture, animal performance and greenhouse emissions on low and high sheep productivity grazing systems: 1-year validation and 25-year analysis

Globally, there is a focus on reducing the absolute methane (CH4) and nitrous oxide emissions, and the emissions intensity (EI, kg CO2e/kg animal product) of livestock production. Increasing the productivity of mixed pasture systems has the potential to increase food (e.g., lamb) and textile fibre (e.g., wool) production while reducing the EI of those products from grazing livestock. The objective of this study was to quantify the differences in greenhouse gas (GHG) emissions and EI between sheep on Low (i.e., low sustainable stocking rate) and High (i.e., high sustainable stocking rate) productivity grazing systems (PGSs). Therefore, a replicated breeding-ewe trial on 18 paddocks was established across 2 - years. Three flocks on Low (3 × 16 ewes/flock) and High PGSs (3 × 32 ewes/flock) rotated across three land-classes and three paddocks per PGS. In year 1, the observed on-farm pasture quantity, quality, and botanical composition, together with lamb BW (kg), and daily CH4 production (DMP, g CH4/head per day) using Open Path Fourier Transformed Infrared (OP-FTIR) spectrometers data were measured. Subsequently, two simulations using GrassGroTM were conducted: (1) a 1-year GrassGroTM simulation that used the observed on-farm data to adjust parameters: date of mating, paddock fertility, and weight of mature ewes to validate GrassGroTM predictions to achieve accuracy and precision targets; and (2) a 25-year (1986-2011) simulation to analyse the effects of Low and High PGSs on sheep production and GHG emissions across a variable climate. The 1-year validation predictions fitted well with the observed on-farm data for: pasture biomass (kg/ha), DM digestibility (%), botanical composition (kg/ha), lamb (kg) product, and DMP (g CH4/head per day). The subsequent predicted results from the 25-year GrassGroTM simulation showed minimal effect of PGS on the mean DM intake (kg DM/day) or DMP for Low and High PGSs, but this was thought to be due to the biomass in both PGSs exceeding 1 500 kg DM/ha. The EI, over the 25-year simulation, on the High PGS was 16.5% lower than the Low PGS. Additional calculations of DMP were conducted using a recent global equation, giving estimates of DMP that closely matched the observed on-farm OP-FTIR DMP measurements, but these were lower than the GrassGroTM predictions and improved the accuracy and precision. It is concluded that in some pasture situations, managing pastures and stock numbers to intensify grazing systems can allow increased livestock production, without increasing daily CH4 emissions/head while substantially decreasing the EI of the animal products generated.

Georeferenced soil provenancing with digital signatures

The provenance or origin of a soil sample is of interest in soil forensics, archaeology, and biosecurity. In all of these fields, highly specialized and often expensive analysis is usually combined with expert interpretation to estimate sample origin. In this proof of concept study we apply rapid and non-destructive spectral analysis to the question of direct soil provenancing. This approach is based on one of the underlying tenets of soil science – that soil pedogenesis is spatially unique, and thus digital spectral signatures of soil can be related directly, rather than via individual soil properties, to a georeferenced location. We examine three different multivariate regression techniques to predict GPS coordinates in two nested datasets. With a minimum of data processing, we show that in most instances Eastings and Northings can be predicted to within 20% of the range of each within the dataset using the spectral signatures produced via portable x-ray fluorescence. We also generate 50 and 95% confidence intervals of prediction and express these as a range of GPS coordinates. This approach has promise for future application in soil and environmental provenancing.

Integrated overview of results from a farmlet experiment which compared the effects of pasture inputs and grazing management on profitability and sustainability

The Cicerone Project conducted a grazed farmlet experiment on the Northern Tablelands of New South Wales, Australia, from July 2000 to December 2006, to address questions raised by local graziers concerning how they might improve the profitability and sustainability of their grazing enterprises. This unreplicated experiment examined three management systems at a whole-farmlet scale. The control farmlet (farmlet B) represented typical management for the region, with flexible rotational grazing and moderate inputs. A second farmlet (farmlet A) also used flexible rotational grazing but had a higher level of pasture renovation and soil fertility, while the third farmlet (farmlet C) had the same moderate inputs as farmlet B but employed intensive rotational grazing. The present paper provides an integrated overview of the results collated from component papers and discusses the inferences that can be drawn from what was a complex, agroecosystem experiment. The measurements recorded both early and late in the experiment were tabulated for each of the farmlets and compared with each other as relative proportions, allowing visual presentation on a common, indexed scale. Because of equivalent starting conditions, there was little difference between farmlets early in the experimental period (2000–01) across a wide array of measured parameters, including herbage mass, potential pasture growth rate, liveweight, wool production per head, stocking rate, gross margin and equity. Although the experiment experienced drier-than-average conditions, marked differences emerged among farmlets over time, due to the effects of treatments. During the latter half of the experimental period (2003–06), farmlet A showed numerous positive and a few negative consequences of the higher rate of pasture renovation and increased soil fertility compared with the other two farmlets. While intensive rotational grazing resulted in superior control of gastrointestinal nematodes and slightly finer wool, this system had few effects on pastures and no positive effects on sheep liveweights, wool production or stocking rate. Whereas farmlet A showed higher gross margins, it had a negative and lower short-term cash position than did farmlets B and C, due largely to the artificially high rate of pasture renovation undertaken on this farmlet during the experiment. Although farmlet B had the highest cash position at the end of the experiment, this came at a cost of the declining quality of its pastures. Modelling of the farmlet systems allowed the results to be considered over the longer timeframes needed to assess sustainability. Thus, returns on investment were compared over realistic amortisation periods and produced outcomes based on long-term climatic expectations which were compared with those that arose under the drier-than-average conditions experienced during the experimental period. The main factors responsible for lifting the productivity of farmlet A were the sowing of temperate species and increased soil fertility, which enhanced the amount of legume and increased pasture quality and potential pasture growth. The factor that affected farmlet C most was the low proportion of the farmlet grazed at any one time, with high stock density imposed during grazing, which decreased feed intake quality. The paper concludes that more profitable and sustainable outcomes are most likely to arise from grazing enterprises that are proactively managed towards optimal outcomes by maintaining sufficient desirable perennial grasses with adequate legume content, enhancing soil fertility and employing flexible rotational grazing.