ORCID Profile
0000-0001-7425-452X
Current Organisation
University of Tasmania
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Publisher: CSIRO Publishing
Date: 2017
DOI: 10.1071/AN16492
Abstract: A priori knowledge of seasonal pasture growth rates helps livestock farmers plan with pasture supply and feed budgeting. Longer forecasts may allow managers more lead time, yet inaccurate forecasts could lead to counterproductive decisions and foregone income. By using climate forecasts generated from historical archives or the global circulation model (GCM) called the Predictive Ocean Atmosphere Model for Australia (POAMA), we simulated pasture growth rates in a whole-farm model and compared growth-rate forecasts with growth-rate hindcasts (viz. retrospective forecasts). Hindcast pasture growth rates were generated using posterior weather data measured at two sites in north-western Tasmania, Australia. Forecasts were made on a monthly basis for durations of 30, 60 and 90 days. Across sites, forecasting approaches and durations, there were no significant differences between simulated growth-rate forecasts and hindcasts when our statistical inference was conducted using either the Kolmogorov–Smirnov statistic or empirical cumulative distribution functions. However, given that both of these tests were calculated by comparing growth-rate hindcasts with monthly distributions of forecasts, we also examined linear correlations between monthly hindcast values and median monthly growth-rate forecasts. Using this approach, we found a higher correlation between hindcasts and median monthly forecasts for 30 days than for 60 or 90 days, suggesting that monthly growth-rate forecasts provide more skilful predictions than forecast durations of 2 or 3 months. The range in monthly growth-rate forecasts at 30 days was less than that at 60 or 90 days, further reinfocing the aforementioned result. The strength of the correlation between growth-rate hindcasts and median monthly forecasts from the historical approach was similar to that generated using POAMA data. Overall, the present study found that (1) statistical methods of comparing forecast data with hindcast data are important, particularly if the former is a distribution whereas the latter is a single value, (2) 1-month growth-rate forecasts have less uncertainty than forecast durations of 2 or 3 months, and (3) there is little difference between pasture growth rates simulated using climate data from either historical records or from GCMs. To test the generality of these conclusions, the study should be extended to other dairy regions. Including more regions would both enable studies of sites with greater intra-seasonal climate variability, but also better highlight the impact of seasonal and regional variation in forecast skill of POAMA as applied in our forecasting methods.
Publisher: Wiley
Date: 24-11-2021
DOI: 10.1111/GCB.15441
Abstract: Simulation models represent soil organic carbon (SOC) dynamics in global carbon (C) cycle scenarios to support climate‐change studies. It is imperative to increase confidence in long‐term predictions of SOC dynamics by reducing the uncertainty in model estimates. We evaluated SOC simulated from an ensemble of 26 process‐based C models by comparing simulations to experimental data from seven long‐term bare‐fallow (vegetation‐free) plots at six sites: Denmark (two sites), France, Russia, Sweden and the United Kingdom. The decay of SOC in these plots has been monitored for decades since the last inputs of plant material, providing the opportunity to test decomposition without the continuous input of new organic material. The models were run independently over multi‐year simulation periods (from 28 to 80 years) in a blind test with no calibration (Bln) and with the following three calibration scenarios, each providing different levels of information and/or allowing different levels of model fitting: (a) calibrating decomposition parameters separately at each experimental site (Spe) (b) using a generic, knowledge‐based, parameterization applicable in the Central European region (Gen) and (c) using a combination of both (a) and (b) strategies (Mix). We addressed uncertainties from different modelling approaches with or without spin‐up initialization of SOC. Changes in the multi‐model median (MMM) of SOC were used as descriptors of the ensemble performance. On average across sites, Gen proved adequate in describing changes in SOC, with MMM equal to average SOC (and standard deviation) of 39.2 (±15.5) Mg C/ha compared to the observed mean of 36.0 (±19.7) Mg C/ha (last observed year), indicating sufficiently reliable SOC estimates. Moving to Mix (37.5 ± 16.7 Mg C/ha) and Spe (36.8 ± 19.8 Mg C/ha) provided only marginal gains in accuracy, but modellers would need to apply more knowledge and a greater calibration effort than in Gen, thereby limiting the wider applicability of models.
Publisher: Elsevier BV
Date: 03-2020
Publisher: Elsevier BV
Date: 09-2023
Publisher: Elsevier BV
Date: 10-2016
Publisher: MDPI AG
Date: 18-07-2022
DOI: 10.3390/IJPB13030017
Abstract: Currently, crop physiological responses to waterlogging are considered only in a few crop models and in a limited way. Here, we examine the process bases of seven contemporary models developed to model crop growth in waterlogged conditions. The representation of plant recovery in these models is over-simplified, while plant adaptation or phenotypic plasticity due to waterlogging is often not considered. Aeration stress conceptualisation varies from the use of simple multipliers in equations describing transpiration and biomass to complex linkages of aeration-deficit factors with root growth, transpiration and nitrogen fixation. We recommend further studies investigating more holistic impacts and multiple stresses caused by plant behaviours driven by soils and climate. A sensitivity analysis using one model (a developer version of APSIM) with default parameters showed that waterlogging has the greatest impact on photosynthesis, followed by phenology and leaf expansion, suggesting a need for improved equations linking waterlogging to carbon assimilation. Future studies should compare the ability of multiple models to simulate real and in situ effects of waterlogging stress on crop growth using consistent experimental data for initialisation, calibration and validation. We conclude that future experimental and modelling studies must focus on improving the extent to which soil porosity, texture, organic carbon and nitrogen and plant-available water affect waterlogging stress, physiological plasticity and the ensuing temporal impacts on phenology, growth and yield.
Publisher: Elsevier BV
Date: 11-2014
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/AN14309
Abstract: Ewes with the fecundity Booroola (FecB) gene produce more lambs per ewe on average than ewes without the gene and offers a potential way to decrease greenhouse gas emissions (net and per unit animal product) without reducing lamb production if the lambs can be reared to market weights. Using a case study farm in south-west Victoria, a biophysical modelling study has previously showed that increased ewe fecundity from 1 to 1.5 lambs per ewe increased production by 27% and reduced net farm emissions by 21% for the same long-term stocking rate. In this study, a whole-farm economic analysis was used to investigate the relative merit of the same case study farm, with high-fecundity ewes, compared with a baseline system that represented a typical prime lamb enterprise in the region. An additional system comprising ewes with high fecundity at a lower stocking rate than the case study farm was also examined. The analysis was undertaken to establish which farm systems represented the most economically efficient use of all the resources that are employed over a run of years, and involved estimating the net present value of annual profits earned by the farm in each scenario, taking into account the total value of capital used. The potential revenue from the sale of carbon credits through the Carbon Farming Initiative was also investigated. After accounting for the additional costs involved, increasing ewe fecundity resulted in an increase in annual whole-farm profit compared with the baseline system, but risk, considered as the variability in farm profit, also increased. Decreasing stocking rate for the high-fecundity system reduced annual operating profit and net present value at a 5% discount rate, but had less risk compared with the higher stocking rate system. While both systems that incorporated high-fecundity ewes reduced greenhouse gas emissions, revenue from the sale of carbon credits was small compared with revenue from the sale of lambs, wool and culled ewes. Despite this, and assuming the required increases in fertility and weaning rates could be achieved consistently on-farm, ewes with high fecundity may offer producers the opportunity to increase production and profit as well as decrease greenhouse gas emissions.
Publisher: Elsevier BV
Date: 07-2019
Publisher: CSIRO Publishing
Date: 2019
DOI: 10.1071/CP18311
Abstract: The profitability of dairying in south-eastern Australia can be improved by increasing pasture production during summer–autumn, when growth rates for the existing perennial ryegrass (Lolium perenne L.) feedbase are low. A study undertaken in cool-temperate north-west Tasmania examined the effect of stubble height and irrigation management on swards of perennial ryegrass, continental (summer-active) tall fescue (Festuca arundinacea Schreb.) and chicory (Cichorium intybus L.). Irrigation treatments included full irrigation (~20mm applied at every 20mm precipitation deficit), deficit irrigation (~20mm applied at alternate full-irrigation events) and rainfed (no irrigation). All species achieved greater summer–autumn yields when repeatedly defoliated to stubble heights of 35 or 55mm than when defoliated to 115mm, irrespective of irrigation treatment. Swards were managed under a common defoliation schedule of nine defoliation events in 12 months. Under full irrigation, second-year tall fescue achieved a greater summer–autumn yield than perennial ryegrass (by 10%, or 0.7 t DM ha–1), highlighting the potential role of tall fescue in north-west Tasmania. This was further demonstrated by the high marginal irrigation water-use index values (1.6–2.7 t DM ML–1) of tall fescue. By contrast, summer–autumn growth achieved by chicory was less than or equal to perennial ryegrass.
Publisher: Research Square Platform LLC
Date: 27-07-2022
DOI: 10.21203/RS.3.RS-1863270/V1
Abstract: Extreme weather events threaten food security, yet global assessments of crop waterlogging are rare. Here, we make three important contributions to the literature. First, we develop a paradigm that distils common stress patterns across environments, genotypes and climate horizons. Second, we embed improved process-based understanding into a contemporary farming systems model to discern changes in global crop waterlogging under future climates. Third, we elicit viable systems adaptations to waterlogging. Using projections from 27 global circulation models, we show that yield penalties caused by waterlogging increased from 3–11% historically to 10–20% by 2080. Altering sowing time and adopting waterlogging tolerant genotypes reduced yield penalties by up to 18%, while earlier sowing of winter genotypes alleviated waterlogging risk by 8%. We show that future stress patterns caused by waterlogging are likely to be similar to those occurring historically, suggesting that adaptations for future climates could be successfully designed using current stress patterns.
Publisher: Wiley
Date: 27-01-2009
DOI: 10.1111/J.1365-3040.2008.01918.X
Abstract: Photosynthetic rate per unit nitrogen generally declines as leaf mass per unit area (LMA) increases. To determine how much of this decline was associated with allocating a greater proportion of leaf nitrogen into cell wall material, we compared two groups of plants. The first group consisted of two species from each of eight genera, all of which were perennial evergreens growing in the Australian National Botanic Gardens (ANBG). The second group consisted of seven Eucalyptus species growing in a greenhouse. The percentage of leaf biomass in cell walls was independent of variation in LMA within any genus, but varied from 25 to 65% between genera. The nitrogen concentration of cell wall material was 0.4 times leaf nitrogen concentration for all species apart from Eucalyptus, which was 0.6 times leaf nitrogen concentration. Between 10 and 30% of leaf nitrogen was recovered in the cell wall fraction, but this was independent of LMA. No trade-off was observed between nitrogen associated with cell walls and the nitrogen allocated to ribulose 1.5-bisphosphate carboxylase/oxygenase (Rubisco). Variation in photosynthetic rate per unit nitrogen could not be explained by variation in cell wall nitrogen.
Publisher: CSIRO Publishing
Date: 2016
DOI: 10.1071/AN15515
Abstract: Here we examine the concordance among emissions, production and gross margins of extensive beef farming systems by modelling a range of scenarios for herd management, animal genotype and pasture nutritive quality. We based our simulations on a case-study farm in central Queensland, Australia, and studied the influence of interventions designed for emissions mitigation, increasing productivity, or increasing gross margin. Interventions included replacing urea supplementation with nitrate, finishing cattle on the perennial forage leucaena (L), herd structure optimisation (HO), higher female fecundity (HF), and a leucaena finishing enterprise that had net farm emissions equal to the baseline (leucaena equal emissions LEE). The HO intervention reduced the ratio of breeding cows relative to steers and unmated heifers, and lowered the ratio of costs to net cattle sales. Gross margin of the baseline, nitrate, L, LEE, HO and HF scenarios were AU$146 000, AU$91 000, AU$153 000, AU$170 000, AU$204 000 and AU$216 000, respectively. Enterprises with early joining of maiden heifers as well as HO and HF further increased gross margin (AU$323 000), while systems incorporating all compatible interventions (HO, HF, early joining, LEE) had a gross margin of AU$315 000. We showed that interventions that increase liveweight turnoff while maintaining net farm emissions resulted in higher gross margins than did interventions that maintained liveweight production and reduced net emissions. A key insight of this work was that the relationship between emissions intensity (emissions per unit liveweight production) or liveweight turnoff with gross margin were negative and positive, respectively, but only when combinations of (compatible) interventions were included in the dataset. For ex le, herd optimisation by reducing the number of breeding cows and increasing the number of sale animals increased gross margin by 40%, but this intervention had little effect on liveweight turnoff and emissions intensity. However, when herd optimisation was combined with other interventions that increased production, gross margins increased and emissions intensity declined. This is a fortuitous outcome, since it implies that imposing more interventions with the potential to profitably enhance liveweight turnoff allows a greater reduction in emissions intensity, but only when each intervention works synergistically with those already in place.
Publisher: MDPI AG
Date: 14-03-2023
DOI: 10.3390/LAND12030680
Abstract: The use of beneficial microbes as biofertilizer has become fundamental in the agricultural sector for their potential role in food safety and sustainable crop production. A field trial was conducted to study the influence of beneficial microbes on the efficiency of organic and inorganic sources. The experiment was conducted in two consecutive years (2008–2009 and 2009–2010) in a farmer’s field at Dargai Malakand Division. A randomized complete block design was used with four replications. The results revealed a significantly higher straw and grain nitrogen concentrations for the treatments receiving 50% N from urea + 50% N from FYM + BM, followed by the treatments receiving 50% N from urea + 50% N from (FYM + PM) + BM and 120 kg N ha−1 from urea fertilizer, respectively. Comparing the relevant treatments with and without BM, an increasing trend in N concentrations in straw and grain was observed with BM. The results revealed the highest grain total nitrogen, straw total nitrogen and total nitrogen uptake by wheat crop for the treatments receiving 120 kg N ha−1 from urea, followed by the treatments receiving 50% N from urea + 50% N from PM + BM and 50% N from urea + 50% N from (FYM + PM) + BM. Moreover, after comparing the relevant treatments with and without BM, for the parameters mentioned, an increasing trend in nitrogen uptake was observed. Significantly higher total soil nitrogen was obtained for treatment with 50% N from urea + 50% N from FYM + BM, followed by the treatment with 50% N from urea + 50% N from (FYM + PM) + BM or 50% N from urea + 50% N from PM + BM, respectively, as compared to the control treatment plot. Markedly higher soil mineral nitrogen was obtained for the 50% N from urea + 50% N from (FYM + PM) + BM treatment, followed by the treatment with 50% N from urea + 50% N from FYM + BM and 50% N treatment from urea + 50% N from PM + BM, compared to the control treatment. Comparing the relevant treatments with and without BM, an increasing trend in total soil N (g kg−1 soil) and soil mineral N (mg kg−1 soil) was noted with BM application. From the results, a significant increase in soil organic matter status (g kg−1 soil) due to application of organic and inorganic fertilization was summarized. Significantly higher soil organic matter (g kg−1 soil) was recorded for the treatment receiving 50% N from urea + 50% N from FYM + BM compared to untreated control plots. Our study further revealed an increasing trend in soil organic matter status (g kg−1 soil) when comparing the relevant treatments with and without BM.
Publisher: CSIRO Publishing
Date: 2019
DOI: 10.1071/CP18313
Abstract: Defoliating pasture to shorter stubble heights (height above the soil surface) may increase temperature at the plant crown (plant–soil interface). This is especially relevant to summer C3 pasture production in parts of south-eastern Australia, where above-optimal ambient temperatures (≥30°C) are often recorded. A rainfed field experiment in north-west Tasmania, Australia, quantified the effect of stubble-height management on the upper distribution of crown temperatures (90th and 75th percentiles) experienced by three pasture species: perennial ryegrass (Lolium perenne L.), tall fescue (Festuca arundinacea Schreb. syn. Schedonorus arundinaceus (Schreb.) Dumort. syn. L. arundinaceum (Schreb.) Darbysh.), and chicory (Cichorium intybus L.). Three stubble-height treatment levels were evaluated: 35, 55 and 115mm. Defoliation to shorter stubble heights (35 or 55mm cf. 115mm) increased the crown temperature of all species in the subsequent regrowth cycle (period between successive defoliation events). In the second summer, defoliating to shorter stubble heights increased the 90th percentile of crown temperature by an average of 4.2°C for perennial ryegrass, 3.6°C for tall fescue and 1.8°C for chicory. Chicory and second-year tall fescue swards experienced less-extreme crown temperatures than perennial ryegrass. This may partly explain why these two species often outyield perennial ryegrass in hotter summer environments than north-west Tasmania, and hence the increasing interest in their use.
Publisher: Elsevier BV
Date: 08-2023
Publisher: MDPI AG
Date: 29-05-2023
DOI: 10.3390/LAND12061142
Abstract: The emergence of cloud computing, big data analytics, and machine learning has catalysed the use of remote sensing technologies to enable more timely management of sustainability indicators, given the uncertainty of future climate conditions. Here, we examine the potential of “regenerative agriculture”, as an adaptive grazing management strategy to minimise bare ground exposure while improving pasture productivity. High-intensity sheep grazing treatments were conducted in small fields (less than 1 ha) for short durations (typically less than 1 day). Paddocks were subsequently spelled to allow pasture biomass recovery (treatments comprising 3, 6, 9, 12, and 15 months), with each compared with controls characterised by lighter stocking rates for longer periods (2000 DSE/ha). Pastures were composed of wallaby grass (Austrodanthonia species), kangaroo grass (Themeda triandra), Phalaris (Phalaris aquatica), and cocksfoot (Dactylis glomerata), and were destructively s led to estimate total standing dry matter (TSDM), standing green biomass, standing dry biomass and tr led biomass. We invoked a machine learning model forced with Sentinel-2 imagery to quantify TSDM, standing green and dry biomass. Faced with La Nina conditions, regenerative grazing did not significantly impact pasture productivity, with all treatments showing similar TSDM, green biomass and recovery. However, regenerative treatments significantly impacted litterfall and tr led material, with high-intensity grazing treatments tr ling more biomass, increasing litter, enhancing surface organic matter and decomposition rates thereof. Pasture digestibility and sward uniformity were greatest for treatments with minimal spelling (3 months), whereas both standing senescent and tr led material were greater for the 15-month spelling treatment. TSDM prognostics from machine learning were lower than measured TSDM, although predictions from the machine learning approach closely matched observed spatiotemporal variability within and across treatments. The root mean square error between the measured and modelled TSDM was 903 kg DM/ha, which was less than the variability measured in the field. We conclude that regenerative grazing with short recovery periods (3–6 months) was more conducive to increasing pasture production under high rainfall conditions, and we speculate that – in this environment - high-intensity grazing with 3-month spelling is likely to improve soil organic carbon through increased litterfall and tr ling. Our study paves the way for using machine learning with satellite imagery to quantify pasture biomass at small scales, enabling the management of pastures within small fields from afar.
Publisher: MDPI AG
Date: 09-2022
DOI: 10.3390/W14172728
Abstract: The Nepalese Sunsari Morang Irrigation district is the lifeblood of millions of people in the Koshi River basin. Despite its fundamental importance to food security, little is known about the impacts of climate change on future irrigation demand and grain yields in this region. Here, we examined the impacts of climate change on the irrigation demand and grain yield of wheat crop. Climate change was simulated using Representative Concentration Pathways (RCPs) of 4.5 and 8.5 for three time horizons (2016–2045, 2036–2065, and 2071–2100) in the Agricultural Production Systems Simulator (APSIM). For the field data’s measured period (2018–2020), we showed that farmers applied only 25% of the irrigation water required to achieve the maximum potential grain yield. Actual yields were less than 50% of the potential yields. Projected irrigation water demand is likely to increase for RCP4.5 (3%) but likely to decrease under RCP8.5 (8%) due to the truncated crop duration and lower maturity biomass by the end of the 21st century. However, simulated yields declined by 20%, suggesting that even irrigation will not be enough to mitigate the severe and detrimental effects of climate change on crop production. While our results herald positive implications for irrigation demand in the region, the implications for regional food security may be dire.
Publisher: Frontiers Media SA
Date: 21-01-2020
Publisher: Elsevier BV
Date: 07-2022
Publisher: CSIRO Publishing
Date: 2015
DOI: 10.1071/CP13380
Abstract: In many regions, livestock are allowed to graze grain crops during their vegetative development, before grain is harvested at crop maturity. Little is known of the effects of grazing on crop microclimate, particularly the effects of defoliation on crown temperatures. Knowledge of such effects is important because temperature is the main factor underpinning crop ontogeny, and ontogeny drives dry matter allocation, leaf appearance rates and the timing of anthesis, which are key determinants of grain yield. The primary aim of this study was to examine the influence of grazing intensity and duration on the crown temperatures of winter wheat crops grown at Canberra, Australia. A secondary aim was to examine the association between crown temperature and phenology. In 2007, wheat cv. Mackellar was grazed at intensity–duration combinations of low–short (LS, 33 sheep/ha for 31 days), heavy–short (HS, 67 sheep/ha for 31 days) or low–long (LL, 33 sheep/ha for 62 days). In 2008, cvv. Mackellar and Naparoo were grazed at the HS intensity-duration. Cubic smoothing splines were fitted to crown temperature data measured between the end of grazing and anthesis to facilitate identification of long-term trends and statistical differences caused by the effects of defoliation on crown temperature. Grazing treatments with greater intensity or longer duration significantly elevated maximum daily crown temperature differences of 6–7°C were common in the month following grazing. Cubic-spline analysis showed that long-term trends in maximum crown temperature of the HS and LL treatments were significantly greater than corresponding temperatures of controls for the entire post-grazing duration. By contrast, effects of grazing on minimum diurnal crown temperature were small. Increasing biomass removal significantly delayed stem elongation and anthesis. We demonstrate that although initial phenological delays caused by defoliation are large, greater diurnal crown temperature fluctuation in grazed crops leads to greater growing degree-day accumulation between the end of grazing and anthesis. This increases the rate of thermal time accumulation during the post-grazing–anthesis period and is likely prominent in driving greater development rates of grazed crops. We further demonstrate that delays in phenology associated with grazing can be largely accounted for by a thermal time constant, with the LS, HS and LL treatments delaying stem elongation by ~52, 141 and 214 degree-days, respectively, above a base temperature of 0°C. Results from these experiments and interpretations herein will be of use in designing crop-grazing regimes, and in studies examining implications of defoliation on vegetative microclimate and on physiological feedback effects caused by elevated temperature.
Publisher: MDPI AG
Date: 18-10-2020
DOI: 10.3390/IJMS21207705
Abstract: The COL7A1 gene encodes homotrimer fibrils essential for anchoring dermal and epidermal layers, and pathogenic mutations in COL7A1 can cause recessive or dominant dystrophic epidermolysis bullosa. As a monogenic disease gene, COL7A1 constitutes a potential target for antisense oligomer-mediated exon skipping, a therapy applicable to a growing number of other genetic disorders. However, certain characteristics of COL7A1: many exons, low average intron size, and repetitive and guanine-cytosine rich coding sequence, present challenges to the design of specific and effective antisense oligomers. While targeting COL7A1 exons 10 and 73 for excision from the mature mRNA, we discovered that antisense oligomers comprised of 2′-O-methyl modified bases on a phosphorothioate backbone and phosphorodiamidate morpholino oligomers produced similar, but distinctive, splicing patterns including excision of adjacent nontargeted exons and/or retention of nearby introns in some transcripts. We found that the nonsequential splicing of certain introns may alter pre-mRNA processing during antisense oligomer-mediated exon skipping and, therefore, additional studies are required to determine if the order of intron removal influences multiexon skipping and/or intron retention in processing of the COL7A1 pre-mRNA.
Publisher: InTech
Date: 16-11-2016
DOI: 10.5772/64827
Publisher: MDPI AG
Date: 13-02-2023
Abstract: Indica–japonica hybrid rice (I–JR) typically has greater grain yield than that of Indica hybrid rice (IR) under prolific shading, but it is not known how shading impacts on physiological characteristics underpinning grain quality. Here, we conducted a two-year field experiment in the mid-reaches of the Yangtze River region using I–JR (genotypes Yongyou 1540 and Yongyou 538) and IR (genotypes Y-liangyou 900 and Quanyouhuazhan). We found that shading reduced grain appearance and quality, particularly milling and heading rates, and chalkiness. Shading disrupted carbon and nitrogen metabolism, impacting traits influencing the human perception of the taste of the grain, such that amylose decreased by 5.9% (I–JR) and 12.9% (IR) grain protein significantly increased, with lesser effects in I–JR than IR under shading. Shading also reduced peak, hot, and final viscosities, and breakdown value. I–JR had improved rice quality compared with that of IR due to the greater propensity of the former to photosynthesize under shading, leading to the improved functioning of carbon and nitrogen metabolism.
Publisher: Elsevier BV
Date: 06-2020
Publisher: Elsevier BV
Date: 2015
Publisher: Elsevier BV
Date: 11-2018
Publisher: CSIRO Publishing
Date: 2016
DOI: 10.1071/AN15296
Abstract: Milking cows typically dominate dairy farm greenhouse gas (GHG) emissions, but replacement heifers also contribute to farm emissions and can increase the emission intensity of milk production. In northern Australia, heifers generally graze poorer-quality subtropical pastures and in the absence of energy-dense supplementary feed during periods of low pasture growth, liveweight (LW) gain can be restricted. This modelling study examined the time required and enteric methane (CH4) emissions produced in raising dairy heifers to a target LW for first mating by feeding a diet assuming either constant (static) or variable (dynamic) nutritive values. Using a static approach (Australian Feeding Standards methodology), and assuming a target mating LW of 360 kg, growing heifers reached their target LW at ~18 months of age while consuming C4 grasses with a constant metabolisable energy content of 9.5 MJ/kg dry matter (DM) or 11 months of age on a diet of 11.0 MJ/kg DM. Enteric CH4 emissions were 1.2 and 0.8 t of carbon dioxide equivalents/heifer over the 18- and 11-month periods, respectively. To explore the extent with which climatic conditions influence seasonal pasture availability and nutritive value with a dynamic approach, we used a whole-farm biophysical model (SGS pasture model) to simulate diets with mean metabolisable energy values of 9.5 and 10.9 MJ/ kg DM. On average (±s.d.), heifers required 22 ± 4 and 17 ± 1 months, respectively, to reach target LW, with cumulative enteric CH4 emissions of 1.22 ± 0.20 and 0.72 ± 0.04 t carbon dioxide equivalents, respectively. The dynamic approach resulted in slower LW gain due to the variable nutritive value of the diet throughout the year, resulting in seasonal periods of LW plateauing or decline. Maintaining heifers on high-quality diets in subtropical northern Australia should result in increased daily LW gain, lower enteric CH4 emissions to mating LW and earlier calving. Together, these factors reduce their lifetime emission intensity of milk production.
Publisher: MDPI AG
Date: 05-06-2022
DOI: 10.3390/LAND11060846
Abstract: Greenhouse gas (GHG) emissions from crop residue management have been studied extensively, yet the effects of harvesting more than one crop residue in a rotation have not been reported. Here, we measured the short-term changes in methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2) emissions in response to residue removal from continuous corn (Zea mays L.) (CC) and corn–wheat (Triticum aestivum L.)–soybean (Glycine max L. Merr.) (CWS) rotations in the Mid-Atlantic USA. A first experiment retained five corn stover rates (0, 3.33, 6.66, 10, and 20 Mg ha−1) in a continuous corn (CC) in Blacksburg, VA, in 2016 and 2017. Two other experiments, initiated during the wheat and corn phases of the CWS rotation in New Kent, VA, utilized a factorial combination of retained corn (0, 3.33, 6.66, and 10.0 Mg ha−1) and wheat residue (0, 1, 2, and 3 Mg ha−1). Soybean residue was not varied. Different crop retention rates did not affect CO2 fluxes in any of the field studies. In Blacksburg, retaining 5 Mg ha−1 stover or more increased CH4 and N2O emissions by ~25%. Maximum CH4 and N2O fluxes (4.16 and 5.94 mg m−2 day−1) occurred with 200% (20 Mg ha−1) retention. Two cycles of stover management in Blacksburg, and one cycle of corn or wheat residue management in New Kent did not affect GHG fluxes. This study is the first to investigate the effects of crop residue on GHG emissions in a multi-crop system in humid temperate zones. Longer-term studies are warranted to understand crop residue management effects on GHG emissions in these systems.
Publisher: Wiley
Date: 03-2022
DOI: 10.1002/GLR2.12010
Abstract: Past assessments report negative impacts of the climate crisis in boreal areas but milder and shorter winters and elevated atmospheric CO 2 may provide opportunities for agricultural productivity potentially playing a significant role in future food security. Arable cropping systems are expanding in boreal areas, but the regional mainstay will likely continue to be livestock production. Agroecological models can when appropriately calibrated and evaluated, facilitate improved productivity while minimising environmental impacts by identifying system interactions, and quantifying greenhouse gas emissions, soil carbon stocks and fertiliser use. While models designed for temperate and tropical zones abound, few are developed specifically for boreal zones, and there is uncertainty around the performance of existing models in boreal areas. We reviewed model performance across boreal environments and management systems. We identified a dearth of modelling studies in boreal regions, with the publication of three or less papers per year since the year 2000, constituting a significant research gap. Models IFSM and BASGRA_N performed best in grassland production, DNDC best in predicting soil N 2 O and NH 3 emissions. No model outperformed all others, strengthening the case for ensemble modelling. Existing agroecological models would be worthy of further evaluation, providing model improvements designed for boreal systems.
Publisher: Springer Science and Business Media LLC
Date: 02-05-2023
DOI: 10.1007/S11625-023-01323-2
Abstract: While society increasingly demands emissions abatement from the livestock sector, farmers are concurrently being forced to adapt to an existential climate crisis. Here, we examine how stacking together multiple systems adaptations impacts on the productivity, profitability and greenhouse gas (GHG) emissions of livestock production systems under future climates underpinned by more frequent extreme weather events. Without adaptation, we reveal that soil carbon sequestration (SCS) in 2050 declined by 45–133%, heralding dire ramifications for CO 2 removal aspirations associated with SCS in nationally determined contributions. Across adaptation-mitigation bundles examined, mitigation afforded by SCS from deep-rooted legumes was lowest, followed by mitigation from status quo SCS and woody vegetation, and with the greatest mitigation afforded by adoption of enteric methane inhibitor vaccines. Our results (1) underline a compelling need for innovative, disruptive technologies that dissect the strong, positive coupling between productivity and GHG emissions, (2) enable maintenance or additional sequestration of carbon in vegetation and soils under the hotter and drier conditions expected in future, and (3) illustrate the importance of holistically assessing systems to account for pollution swapping, where mitigation of one type of GHG (e.g., enteric methane) can result in increased emissions of another (e.g., CO 2 ). We conclude that transdisciplinary participatory modelling with stakeholders and appropriate bundling of multiple complementary adaptation-mitigation options can simultaneously benefit production, profit, net emissions and emissions intensity.
Publisher: Cambridge University Press (CUP)
Date: 14-01-2016
DOI: 10.1017/S0021859615001185
Abstract: A warmer and potentially drier future climate is likely to influence the production of forage crops on dairy farms in the southeast dairy regions of Australia. Biophysical modelling was undertaken to explore the resilience of forage production of in idual forage crops to scalar increases in temperature, atmospheric carbon dioxide (CO 2 ) concentration and changes in daily rainfall. The model APSIM was adapted to reflect species specific responses to growth under elevated atmospheric CO 2 concentrations. It was then used to simulate 40 years of production of forage wheat, oats, annual ryegrass, maize grown for silage, forage sorghum, forage rape and alfalfa grown at three locations in southeast Australia with increased temperature scenarios (1, 2, 3 and 4 °C of warming) and atmospheric CO 2 concentration (435, 535, 640 and 750 ppm) and decreasing rainfall scenarios (10, 20 or 30% less rainfall). At all locations positive increases in DM yield compared with the baseline climate scenario were predicted for lucerne (2·6–93·2% increase), wheat (8·9–37·4% increase), oats (6·1–35·9% increase) and annual ryegrass (9·7–66·7% increase) under all future climate scenarios. The response of forage rape and forage sorghum varied between location and climate change scenario. At all locations, maize was predicted to have a minimal change in yield under all future climates (between a 2·6% increase and a 6·8% decrease). The future climate scenarios altered the seasonal pattern of forage supply for wheat, oats and lucerne with an increase in forage produced during winter. The resilience of forage crops to climate change indicates that they will continue to be an important component of dairy forage production in southeastern Australia.
Publisher: MDPI AG
Date: 11-2022
DOI: 10.3390/LAND11111947
Abstract: With global warming, arable land in boreal regions is tending to expand into high latitude regions in the northern hemisphere. This entails certain risks such that inappropriate management could result in previously stable carbon sinks becoming sources. Agroecological models are an important tool for assessing the sustainability of long-term management, yet applications of such models in boreal zones are scarce. We collated eddy-covariance, soil climate and biomass data to evaluate the simulation of GHG emissions from grassland in eastern Finland using the process-based model DNDC. We simulated gross primary production (GPP), net ecosystem exchange (NEE) and ecosystem respiration (Reco) with fair performance. Soil climate, soil temperature and soil moisture at 5 cm were excellent, and soil moisture at 20 cm was good. However, the model overestimated NEE and Reco following crop termination and tillage events. These results indicate that DNDC can satisfactorily simulate GHG fluxes in a boreal grassland setting, but further work is needed, particularly in simulated second biomass cuts, the ( cm) soil layers and model response to management transitions between crop types, cultivation, and land use change.
Publisher: Elsevier BV
Date: 04-2019
Publisher: American Geophysical Union (AGU)
Date: 12-2020
DOI: 10.1029/2020EF001801
Publisher: CSIRO Publishing
Date: 2016
DOI: 10.1071/AN15578
Abstract: Significant research has been conducted on greenhouse gas emissions mitigation techniques for ruminant livestock farming, however putting these techniques into practice on-farm requires consideration of adoptability by livestock producers. We modelled the adoptability of a range of livestock greenhouse gas abatement techniques using data from farm case studies and industry surveys, then compared the effectiveness of several techniques in reducing emissions intensity and net farm emissions. The influence of the Australian Government Emissions Reduction Fund on adoptability was included by modelling techniques with and without the requirements of an Australian Government Emissions Reduction Fund project. Modelled adoption results were compared with data obtained from surveys of livestock farmers in northern Tasmania, Australia. Maximum adoption levels of the greenhouse gas mitigation techniques ranged from 34% to 95% and the time required to reach 90% of the peak adoption levels ranged from 3.9 to 14.9 years. Techniques with the lowest adoption levels included providing supplements to optimise rumen energy : protein ratio and feeding high-lipid diets. Techniques with the highest adoptability involved improved ewe reproductive efficiency, with more fertile flocks having higher adoption rates. Increasing liveweight gain of young stock so animals reached slaughter liveweight 5–7 weeks earlier (early finishing) and joining maiden ewes at 8 months instead of 18 months had the fastest adoption rates. Techniques which increased net emissions and reduced emissions per liveweight sold (emissions intensity) had higher adoptability due to profit advantages associated with greater meat and wool production, whereas some techniques that reduced both net emissions and emissions intensity had lower adoptability and/or longer delays before peak adoption because of complexity and costs associated with implementation, or lack of extension information. Techniques that included an Australian Government Emissions Reduction Fund project had reduced maximum adoption levels and reduced rate of adoption due to difficulty of implementation and higher cost. Adopting pastures with condensed tannins reduced net emissions, emissions intensity and had high adoption potential, but had a long delay before peak adoption levels were attained, suggesting the technique may be worthy of increased development and extension investment. These results will be of benefit to livestock farmers, policymakers and extension practitioners. Programs designed to mitigate livestock greenhouse gas should consider potential adoption rates by agricultural producers and time of implementation before embarking on new research themes.
Publisher: Wiley
Date: 21-12-2021
DOI: 10.1111/AJR.12807
Abstract: The objective of this study was to determine the impact of a new salaried medical officer position on health service provision and organisational performance. Health service staff were invited to complete a survey to ascertain their overall satisfaction with the salaried medical officer position and impact on their workflow. Purposive s ling identified respondents for interviews to further explore the experiences of health service staff. Financial, administrative and quality information was extracted for analysis. Medium size rural health service in Victoria, Australia. All general practitioner, nursing and allied health staff employed by, or who provide services to, the health service. Satisfaction with the salaried medical officer position, ability to address patient concerns, themes from interviews, organisational performance data. Forty surveys (general practitioner, nursing and allied health) were returned and 10 interviews completed. The mean rating for satisfaction with the salaried medical officer position was 8.4 out of 10. Addressing patient care concerns was rated significantly easier by nursing and allied health staff when the salaried medical officer was working. The interviews identified three broad themes: improved efficiency, increased accessibility and eliminated service gaps. Health service staff reported that a salaried medical officer position at a rural health service improved work efficiency, increased accessibility to timely medical advice and improved quality of care, particularly patients at risk of sudden deterioration.
Publisher: Springer Science and Business Media LLC
Date: 10-02-0002
DOI: 10.1038/S41467-023-36129-4
Abstract: Extreme weather events threaten food security, yet global assessments of impacts caused by crop waterlogging are rare. Here we first develop a paradigm that distils common stress patterns across environments, genotypes and climate horizons. Second, we embed improved process-based understanding into a farming systems model to discern changes in global crop waterlogging under future climates. Third, we develop avenues for adapting cropping systems to waterlogging contextualised by environment. We find that yield penalties caused by waterlogging increase from 3–11% historically to 10–20% by 2080, with penalties reflecting a trade-off between the duration of waterlogging and the timing of waterlogging relative to crop stage. We document greater potential for waterlogging-tolerant genotypes in environments with longer temperate growing seasons (e.g., UK, France, Russia, China), compared with environments with higher annualised ratios of evapotranspiration to precipitation (e.g., Australia). Under future climates, altering sowing time and adoption of waterlogging-tolerant genotypes reduces yield penalties by 18%, while earlier sowing of winter genotypes alleviates waterlogging by 8%. We highlight the serendipitous outcome wherein waterlogging stress patterns under present conditions are likely to be similar to those in the future, suggesting that adaptations for future climates could be designed using stress patterns realised today.
Publisher: CSIRO Publishing
Date: 2016
DOI: 10.1071/AN15575
Abstract: Agriculture produces an estimated 14.5% of global anthropogenic greenhouse gases, with livestock emissions being the largest source of enteric methane. Reducing greenhouse gas (GHG) emissions from production and processing of beef cattle will become increasingly important with time, particularly in line with global efforts to mitigate rising GHG emissions. The present study compared several GHG emission scenarios from beef cattle grazing on irrigated Leucaena leucocephala (Lam.) de Wit cv. Cunningham (leucaena) in Queensland, Australia. Animals began grazing the leucaena paddocks when they were 16 months old and continued until ~240 days, before being sold to market. Three scenarios were modelled with cattle grazing leucaena and the resulting GHG emissions calculated, representing (1) the current leucaena paddock (current leucaena scenario), (2) clearing native vegetation and extending the leucaena paddock (extended leucaena scenario) and (3) extending the leucaena paddock onto previously cleared paddocks (alternative leucaena scenario). These were compared with a pre-scenario baseline, where the steers grazed on native vegetation until the time of sale. Herd GHG emission intensities (EI) were reduced in comparison with the baseline (EI of 8.4 tCO2-e/t liveweight sold) for all the leucaena scenarios, where reductions were modelled for the current, extended and alternative leucaena scenarios, which had an EI of 3.9, 3.7 and 3.6 tCO2-e/ t liveweight sold, respectively. Reductions were attributed to the higher growth rates of the steers on leucaena and the anti-methanogenic potential of leucaena. Where leucaena was planted on previously cleared paddocks, carbon stocks (t C/ha) nearly doubled a decade following planting, with most carbon sequestered in the soil. However, total carbon stocks on the property reduced over the modelled period (112 years), where native vegetation, e.g. eucalyptus woodland, was cleared for leucaena planting, but soil carbon yield increased. The combined sequestration of leucaena and the reduction of GHG emission intensities resulted in overall net reductions of GHG emissions for the three leucaena scenarios compared with the baseline. These results demonstrated that the use of leucaena for grazing can be an effective means for farmers to reduce the GHG emissions and increase productivity of their herds. The study also demonstrated that it would take 9 years of reduced emissions to compensate for the carbon lost as emissions from clearing the eucalyptus woodland, suggesting that farmers should use other methods of intensifying production from existing leucaena paddocks if their sole purpose is short-term emissions abatement.
Publisher: MDPI AG
Date: 21-12-2022
Abstract: The super hybrid rice breeding program in China has raised genetic yield ceilings through morphological improvements and inter-subspecific heterosis. Despite this, little information on the physiological basis underlying this yield transformation exists, and less so on the genotype x environment x management conditions enabling consistent yield gains. Here, we assess grain yield, photosynthetic physiology, and leaf carbon and nitrogen (N) metabolic properties of super rice (Y-liangyou900) under four management practices (i.e., zero-fertilizer control, CK farmers’ practice, FP high-yield and high-efficiency management, OPT1 and super-high-yield management, OPT2) using a field experiment conducted over five years. Grain yield and agronomic N use efficiency (AEN) of OPT2 were 15% and 10% higher than OPT1, and 30% and 78% higher than FP, respectively. The superior yields of OPT2 were attributed to higher source production capacity, that is, higher leaf photosynthetic rate, carbon metabolic enzyme activity (i.e., AGP and SPS), nitrogen metabolic enzyme activity (i.e., NR, GS, and GOGAT), soluble protein and sugar content, and delayed leaf senescence (the latter due to elevated activity of protective enzyme systems) during grain filling. The higher AEN of OPT2 was associated with higher activity of leaf carbon metabolic enzyme (i.e., AGP and SPS), nitrogen metabolic enzyme (i.e., NR, GS, GDH, and GOGAT) and protective enzyme (POD) after heading, and lower C/N ratio in grains. We conclude that optimized management (optimized water and fertilizer management with appropriate dense planting) improved grain yield and N use efficiency simultaneously by enhancing post-heading leaf carbon and N metabolism and delayed leaf senescence.
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/CP14088
Abstract: Climatic variability in dryland production environments (E) generates variable yield and crop production risks. Optimal combinations of genotype (G) and management (M) depend strongly on E and thus vary among sites and seasons. Traditional crop improvement seeks broadly adapted genotypes to give best average performance under a standard management regime across the entire production region, with some subsequent manipulation of management regionally in response to average local environmental conditions. This process does not search the full spectrum of potential G × M × E combinations forming the adaptation landscape. Here we examine the potential value (relative to the conventional, broad adaptation approach) of exploiting specific adaptation arising from G × M × E. We present an in-silico analysis for sorghum production in Australia using the APSIM sorghum model. Crop design (G × M) is optimised for subsets of locations within the production region (specific adaptation) and is compared with the optimum G across all environments with locally modified M (broad adaptation). We find that geographic subregions that have frequencies of major environment types substantially different from that for the entire production region show greatest advantage for specific adaptation. Although the specific adaptation approach confers yield and production risk advantages at industry scale, even greater benefits should be achievable with better predictors of environment-type likelihood than that conferred by location alone.
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/AN14436
Abstract: Ruminant livestock are generally considered inefficient converters of dietary nitrogen (N) into animal product. Animal nitrogen use efficiency (NUE) is a measure of the relative transformation of feed N into product and in dairy systems this is often expressed as milk N per unit of N intake (g milk N/100 g N intake). This study was a theoretical exercise to explore the relative potential efficacy and value proposition of breeding versus feeding to improve NUE, reduce urinary N excretion and associated environmental impact in pasture-based dairy systems. The biophysical whole farm systems model DairyMod was used across three dairying regions of south-eastern Australia representing a high-rainfall cool temperate climate (HRCT), a high-rainfall temperate climate (HRT) and a medium-rainfall temperate climate (MRT) to examine the two theoretical approaches of (1) maintaining the same amount of N exported in milk from a reduced N intake and (2) increasing the amount of N exported in milk for the same amount of dietary N intake. Sixteen scenarios were explored for each site these include four supplementary feed N (SN) concentrations (ranging from 1% to 4% N) combined with four milk N (MN) concentrations (ranging from 0.50% to 0.65% N). Reducing the SN concentration from 4% to 1% increased the 30-year mean model-predicted NUEs from ~16 g milk N/100 g N intake at all three sites to between 23 and 28 g milk N/100 g N intake, with the least and greatest improvements in NUE occurring for the HRCT and MRT sites, respectively. Corresponding to this improved NUE through reduced SN concentrations, model-predicted N2O emissions declined from 3.0 to 1.3 t carbon dioxide equivalents (CO2-e)/ha.annum for the HRCT site, from 4.2 to 2.1 t CO2-e/ha.annum for the HRT site and from 4.4 to 2.1 t CO2-e/ha.annum for the MRT site, representing a decline of between 50% and 57%. In contrast, increasing the MN concentration from 0.50% to 0.65% increased the 30-year mean model-predicted NUEs from 17 to 22 g milk N/100 g N intake for the HRCT site, from 18 to 23 g milk N/100 g N intake for the HRT site and from 18 to 24 g milk N/100 g N intake for the MRT site. Corresponding to the improved NUE through increased MN concentrations, model-predicted N2O emissions declined from 2.3 to 2.0 t CO2-e/ha.annum for the HRCT site, from 3.3 to 3.1 t CO2-e/ha.annum for the HRT site and from 3.4 to 3.2 t CO2-e/ha.annum for the MRT site representing a decline of between 7% and 11%. These results suggest that improving animal NUE to reduce associated N2O losses holds much more promise if achieved through a reduction in the amount of N in supplementary feed than through increasing N exported in milk. This is an important finding for the Australian dairy industry, since manipulation of dietary N to better balance the energy to protein ratio would be much easier to implement than manipulation of N concentration in milk through genetics.
Publisher: CSIRO Publishing
Date: 2016
DOI: 10.1071/AN15327
Abstract: Greenhouse gas emissions (GHG) from broadacre sheep farms constitute ~16% of Australia’s total livestock emissions. To study the ersity of Australian sheep farming enterprises a combination of modelling packages was used to calculate GHG emissions from three sheep enterprises (Merino ewe production for wool and meat, Merino-cross ewes with an emphasis on lamb production, and Merino wethers for fine wool production) at 28 sites across eight climate zones in southern Australia. GHG emissions per ha, per dry sheep equivalents and emissions intensity (EI) per tonne of clean wool or liveweight sold under different pasture management or animal breeding options (that had been previously determined in interviews with farmers) were assessed relative to baseline farms in each zone (‘Nil’ option). Increasing soil phosphorus fertility or sowing 40% of the farm area to lucerne resulted in the smallest and largest changes in GHG/dry sheep equivalents, respectively (–66%, 113%), though both of these options had little influence on EI for either clean wool or liveweight sold. Breeding ewes with greater body size or genotypes with higher fleece weight resulted in 11% and 9% reductions, respectively, in EI. Enterprises specialising in lamb production (crossbred ewes) had 89% lower EI than enterprises specialising in fine wool production (Merino wethers). Thus, sheep producers aiming for lower EI could focus more on liveweight turnoff than wool production. Emissions intensities were typically highest in cool temperate regions with high rainfall and lowest in semiarid and arid regions with low aboveground net primary productivity. Overall, animal breeding options reduced EI more than feedbase interventions.
Publisher: MDPI AG
Date: 18-10-2022
DOI: 10.3390/LAND11101825
Abstract: The adoption of eco-friendly fertilizers is increasingly perceived as a sustainable avenue for improving the quantity and quality of medicinal and aromatic plants. Here, we investigated how intercropping and bio-fertilizer application impacted the productivity and essential oil quality of mung bean and marjoram. Treatments were conducted using mung bean monocropping (MBm) and marjoram monocropping (Om), as well as additive intercropping ratios (100% marjoram + 15% mung bean (O/15MB), 100% marjoram + 30% mung bean (O/30MB), 100% marjoram + 45% mung bean (O/45MB), 100% marjoram + 60% mung bean (O/60MB)), each with/without application of biofertilizers (mycorrhiza fungi and bacteria fertilizer). We found that N, P and K content in marjoram and mung bean was highest in the intercropped O/30MB and O/45MB. The maximum land equivalent ratio (LER) index (1.6) was recorded for the O/15MB treatment following biofertilizer application, indicating that 59% more area in the monocropping treatment would be required to achieve the same yield as for the intercropping treatments. The maximum content of carvacrol, p-cymene and carvacrol methyl ether was obtained for the O/45MB treatment under biofertilizer. These results indicate that intercropping of marjoram/mung bean (especially O/45MB) along with biofertilizer application may pave the way towards more sustainable agronomy for improving essential oil quantity and quality.
Publisher: CSIRO Publishing
Date: 2019
DOI: 10.1071/CP18566
Abstract: The nitrogen (N) nutrition of dairy pasture systems in southern Australia has changed from almost total dependence on legumes in the early 1990s through to almost complete reliance on N fertiliser today. Although some tactical N fertiliser is applied to sheep and beef pastures to boost late winter growth, most N fertiliser usage on pastures remains with the dairy industry. Intensification of the farming system, through increased stocking rates and a greater reliance on N fertiliser, has increased N loading, leading to higher potential N losses through volatilisation, leaching and denitrification. With increasing focus on the environmental impact of livestock production, reducing N loading on dairy farms will become increasingly important to the longer-term sustainability of the dairy industry, possibly with the expectation that Australia will join most of the developed countries in regulating N loading in catchments. This paper examines N usage in modern pasture-based dairy systems, the N cycle and loss pathways, and summarises a series of recent modelling studies and component research, investigating options for improving N use efficiency (NUE) and reducing whole-farm N balance. These studies demonstrate that the application of revised practices has the potential to improve NUE, with increasing sophistication of precision technologies playing an important role. This paper discusses the challenge of sustainably intensifying grazing systems with regard to N loading and what approaches exist now or have the potential to decouple the link between production, fertiliser use and environmental impact.
Publisher: MDPI AG
Date: 08-10-2023
DOI: 10.3390/RS15194866
Publisher: Elsevier BV
Date: 10-2018
Publisher: MDPI AG
Date: 25-10-2023
Publisher: MDPI AG
Date: 07-01-2022
Abstract: Global warming and altered precipitation patterns pose a serious threat to crop production in the North China Plain (NCP). Quantifying the frequency of adverse climate events (e.g., frost, heat and drought) under future climates and assessing how those climatic extreme events would affect yield are important to effectively inform and make science-based adaptation options for agriculture in a changing climate. In this study, we evaluated the effects of heat and frost stress during sensitive phenological stages at four representative sites in the NCP using the APSIM-wheat model. climate data included historical and future climates, the latter being informed by projections from 22 Global Climate Models (GCMs) in the Coupled Model Inter-comparison Project phase 6 (CMIP6) for the period 2031–2060 (2050s). Our results show that current projections of future wheat yield potential in the North China Plain may be overestimated after more accurately accounting for the effects of frost and heat stress in the model, yield projections for 2031-60 decreased from 31% to 9%. Clustering of common drought-stress seasonal patterns into key groups revealed that moderate drought stress environments are likely to be alleviated in the future, although the frequency of severe drought-stress environments would remain similar (25%) to that occurring under the current climate. We highlight the importance of mechanistically accounting for temperature stress on crop physiology, enabling more robust projections of crop yields under future the burgeoning climate crisis.
Publisher: Elsevier BV
Date: 07-2017
Publisher: Springer Science and Business Media LLC
Date: 30-09-2021
DOI: 10.1038/S41597-021-01006-6
Abstract: We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field c aigns, published literature, taxonomic monographs, and in idual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised in idual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge.
Publisher: Elsevier BV
Date: 12-2023
Publisher: Wiley
Date: 18-01-2023
DOI: 10.1002/PPP3.10354
Abstract: Despite comprising a small proportion of global agricultural land use, irrigated agriculture is enormously important to the global agricultural economy. Burgeoning food demand driven by population growth—together with reduced food supply caused by the climate crisis—is polarising the existing tension between water used for agricultural production versus that required for environmental conservation. We show that sustainable intensification via more erse crop rotations, more efficient water application infrastructure and greater farm area under irrigation is conducive to greater farm business profitability under future climates. Research aimed at improving crop productivity often does not account for the complexity of real farms underpinned by land‐use changes in space and time. Here, we demonstrate how a new framework— WaterCan Profit —can be used to elicit such complexity using an irrigated case study farm with four whole‐farm adaptation scenarios ( Baseline , Diversified , Intensified and Simplified ) with four types of irrigated infrastructure ( Gravity , Pipe & Riser , Pivot and Drip ). Without adaptation, the climate crisis detrimentally impacted on farm profitability due to the combination of increased evaporative demand and increased drought frequency. Whole‐farm intensification—via greater irrigated land use, incorporation of rice, cotton and maize and increased nitrogen fertiliser application—was the only adaptation capable of raising farm productivity under future climates. Diversification through incorporation of grain legumes into crop rotations significantly improved profitability under historical climates however, profitability of this adaptation declined under future climates. Simplified systems reduced economic risk but also had lower long‐term economic returns. We conclude with four key insights: (1) When assessing whole‐farm profit, metrics matter: Diversified systems generally had higher profitability than Intensified systems per unit water, but not per unit land area (2) gravity‐based irrigation infrastructure required the most water, followed by sprinkler systems, whereas Drip irrigation used the least water (3) whole‐farm agronomic adaptation through management and crop genotype had greater impact on productivity compared with changes in irrigation infrastructure and (4) only whole‐farm intensification was able to raise profitability under future climates.
Publisher: Wiley
Date: 24-11-2018
DOI: 10.1111/GCB.13965
Abstract: Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N
Publisher: MDPI AG
Date: 28-04-2023
DOI: 10.20944/PREPRINTS202304.1131.V1
Abstract: The emergence of cloud computing, big data analytics, and machine learning has catalysed the use of remote sensing technologies to enable more timely land management of sustainability indicators such as ground cover and grassland biomass, given the uncertainty of future climate and drought conditions. Here, we examine the potential of “regenerative agriculture”, as an adaptive grazing management strategy to minimise bare ground exposure while maximising pasture biomass productivity. High-intensity sheep grazing treatments were conducted in small fields (less than 1 hectare) for short durations (typically less than 1 day). Paddocks were subsequently spelled to allow pasture biomass recovery (treatments comprising 3, 6, 9, 12, and 15 months) with each compared with control treatments with lighter stocking rates for longer periods (2,000 DSE). Pastures were composed of wallaby grass (Austrodanthonia species), kangaroo grass (Themeda triandra), Phalaris (Phalaris aquatica, and cocksfoot (Dactylis glomerata) were destructively s led to estimate total standing dry matter (TSDM), standing green biomass, standing dry biomass and tr led biomass. We then invoked a machine learning model using Sentinel-2 imagery to quantify TSDM, standing green biomass and standing dry biomass. Faced with La Nina conditions, regenerative grazing did not significantly impact pasture productivity, with all treatments showing similar TSDM and green biomass. However, regenerative treatments significantly impacted litter fall and tr led material, with the high intensity grazing treatments causing more dry matter tr ling, increasing litter, enhancing decomposition rates and surface organic matter. Pasture digestibility was greatest for treatments with minimal spelling (3 months), whereas both standing senescent and tr led material were significantly greater for the treatment with 15-month spell periods. Estimates of TSDM using machine learning with Sentinel-2 imagery underestimated TSDM in treatment plots but explained spatiotemporal variability associated within and across treatments. The root mean square error between the measured and modelled TSDM was 903 kg DM/ha, which was less than the variability measured in the field. We conclude that regenerative grazing with short recovery periods (3-6 months) are most conducive to increasing pasture production under high rainfall conditions, and we speculate that high intensity grazing is likely to positively impact on soil organic carbon through increased litterfall and tr ling. Our study paves the way forward for using machine learning with satellite imagery to quantify pasture biomass at small scales, enabling management of pastures from afar.
Publisher: Elsevier BV
Date: 06-2015
Publisher: Research Square Platform LLC
Date: 02-06-2023
DOI: 10.21203/RS.3.RS-2939816/V1
Abstract: Land managers are challenged with balancing priorities for agri-food production, greenhouse gas (GHG) abatement, natural conservation, social and economic license to operate. We co-designed pathways for transitioning farming systems to net-zero emissions under future climates. Few interventions enhanced productivity and profitability while also reducing GHG emissions. Seaweed ( Asparagopsis ) feed supplement and planting trees enabled the greatest mitigation (67–95%), while enterprise ersification (installation of wind turbines) and improved feed-conversion efficiency (FCE) were most conducive to improved profitability (17–39%). Mitigation efficacy was h ered by adoptability. Serendiptiously, the least socially acceptable option – business as usual and purchasing carbon credits to offset emissions – were also the most costly options. In contrast, stacking synergistic interventions enabling enteric methane mitigation, improved FCE and carbon removals entirely negated net emissions in a profitable way. We conclude that costs of transitioning to net-zero vary widely (-64% to + 30%), depending on whether interventions are stacked and/or elicit productivity co-benefits.
Publisher: MDPI AG
Date: 13-04-2023
DOI: 10.3390/AGRICULTURE13040862
Abstract: Abiotic stress imposed by heavy metals (HMs) adversely influences plant growth. In crop plants, such stresses penalize grain yield and ultimately could have enduring connotations for sustainable food security. Although copper (Cu) is an essential micronutrient for crop life, excessive availability of copper impairs plant growth and/or reproductive performance. Anecdotal evidence suggests that hydrogen peroxide (H2O2) is produced in plants under either biotic or abiotic stresses to mitigate oxygen-derived cell toxicity, although the influence of H2O2 remains to be definitively quantified. Here, our aim was to investigate the effects of hydrogen peroxide (H2O2) on the growth, grain yield, and yield components, as well as copper uptake of stressed wheat grown in sandy soil. We found that applications rates of 150 or 300 mg Cu kg−1 soil significantly reduced net photosynthesis, leaf area, chlorophyll, and grain yield. Foliar application of H2O2 to plants grown under 150 and 300 mg Cu kg−1 soil had improved growth, physiological, and yield traits. For instance, foliar application of H2O2 Cu-stressed plants grown under 300 mg Cu kg−1 soil reduced detrimental effects of Cu toxicity by −12% in terms of grains per spike and −7% for 1000-grain weight in comparison to the control treatment. Foliar application of H2O2 on wheat grown under copper stress reduced accumulation of other heavy metals such as cadmium. We suggest that the potential for foliar application of H2O2 in mitigating heavy metal stress in crop plants has large global potential however, further work is required to elucidate the environmental conditions and application rates required to attain optimal benefit.
Publisher: American Physiological Society
Date: 15-01-2012
Abstract: The existence and role of fine-temporal structure in the spiking activity of central neurons is the subject of an enduring debate among physiologists. To a large extent, the problem is a statistical one: what inferences can be drawn from neurons monitored in the absence of full control over their presynaptic environments? In principle, properly crafted res ling methods can still produce statistically correct hypothesis tests. We focus on the approach to res ling known as jitter. We review a wide range of jitter techniques, illustrated by both simulation experiments and selected analyses of spike data from motor cortical neurons. We rely on an intuitive and rigorous statistical framework known as conditional modeling to reveal otherwise hidden assumptions and to support precise conclusions. Among other applications, we review statistical tests for exploring any proposed limit on the rate of change of spiking probabilities, exact tests for the significance of repeated fine-temporal patterns of spikes, and the construction of acceptance bands for testing any purported relationship between sensory or motor variables and synchrony or other fine-temporal events.
Publisher: MDPI AG
Date: 03-08-2023
Abstract: The remarkable yield performance of super hybrid rice has played a crucial role in ensuring global food security. However, there is a scarcity of studies investigating the contribution of radiation use efficiency (RUE) to hybrid rice yields under different nitrogen and potassium treatments. In this three-year field experiment, we aimed to evaluate the impact of two hybrid rice varieties (Y-liangyou 900: YLY900 and Quanyouhuazhan: QYHZ) under varying nitrogen regimes (N90: 90 kg N ha−1, N120: 120 kg N ha−1, N180: 180 kg N ha−1) and potassium regimes (K120: 120 kg K2O ha−1, K160: 160 kg K2O ha−1, K210: 210 kg K2O ha−1) on grain yield and its physiological determinants, including RUE, intercepted photosynthetically active radiation (IPAR), aboveground biomass production, and harvest index (HI). Our results revealed that both rice varieties exhibited significantly higher yields when coupled with nitrogen and potassium fertilization. Compared to the N90 × K120 treatment, the N120 × K160 and N180 × K210 combinations resulted in substantial increases in grain yield (12.0% and 21.1%, respectively) and RUE (11.9% and 21.4%, respectively). The YLY900 variety showed notable yield improvement due to enhanced aboveground biomass production resulting from increased IPAR and RUE. In contrast, the QYHZ variety’s aboveground biomass accumulation was primarily influenced by RUE rather than IPAR, resulting in higher RUE and grain yields of 9.2% and 5.3%, respectively, compared to YLY900. Importantly, fertilization led to significant increases in yield, biomass, and RUE, while HI remained relatively constant. Both varieties demonstrated a positive relationship between grain yield and IPAR and RUE. Multiple regression analysis indicated that increasing RUE was the primary driver of yield improvement in hybrid rice varieties. By promoting sustainable agriculture and enhancing fertilizer management, elevating nitrogen and potassium levels from a low base would synergistically enhance rice yield and RUE, emphasizing the critical importance of RUE in hybrid rice productivity compared to HI.
Publisher: MDPI AG
Date: 08-02-2021
DOI: 10.3390/RS13040603
Abstract: Effective dairy farm management requires the regular estimation and prediction of pasture biomass. This study explored the suitability of high spatio-temporal resolution Sentinel-2 imagery and the applicability of advanced machine learning techniques for estimating aboveground biomass at the paddock level in five dairy farms across northern Tasmania, Australia. A sequential neural network model was developed by integrating Sentinel-2 time-series data, weekly field biomass observations and daily climate variables from 2017 to 2018. Linear least-squares regression was employed for evaluating the results for model calibration and validation. Optimal model performance was realised with an R2 of ≈0.6, a root-mean-square error (RMSE) of ≈356 kg dry matter (DM)/ha and a mean absolute error (MAE) of 262 kg DM/ha. These performance markers indicated the results were within the variability of the pasture biomass measured in the field, and therefore represent a relatively high prediction accuracy. Sensitivity analysis further revealed what impact each farm’s in situ measurement, pasture management and grazing practices have on the model’s predictions. The study demonstrated the potential benefits and feasibility of improving biomass estimation in a cheap and rapid manner over traditional field measurement and commonly used remote-sensing methods. The proposed approach will help farmers and policymakers to estimate the amount of pasture present for optimising grazing management and improving decision-making regarding dairy farming.
Publisher: Springer Science and Business Media LLC
Date: 16-03-2019
Publisher: IOP Publishing
Date: 21-03-2022
Abstract: Enabling crop flowering within an optimal calendar window minimises long-term risk of abiotic stress exposure, improving prospects for attaining potential yield. Here, we define the optimal flowering period (OFP) as the calendar time in which long-term risk of frost, water and heat stress are collectively minimised. Using the internationally-renowned farming systems model Agricultural Systems Production Systems sIMulator, we characterised combined effects of climate change and extreme climatic events on the OFPs of barley, durum wheat, canola, chickpeas, fababean and maize from 1910 to 2021. We generate response surfaces for irrigated and dryland conditions using a range of representative sowing times for early and late maturity genotypes. Global warming truncated crop lifecycles, shifting forward flowering of winter crops by 2–43 d in dryland environments, and by −6–19 d in environments with irrigation. Alleviation of water stress by irrigation delayed OFPs by 3–25 d or 11–30 d for early and late maturity winter crops, respectively, raising average yields of irrigated crops by 44%. Even so, irrigation was unable to completely negate the long-term yield penalty caused by the climate crisis peak yields respectively declined by 24% and 13% for rainfed and irrigated crops over the 111 years simulation duration. We conclude with two important insights: (a) use of irrigation broadens OFPs, providing greater sowing time flexibility and likelihood of realising potential yields compared with dryland conditions and (b), the most preferable maturity durations for irrigated winter and summer crops to maximise potential yields are early-sown long-season (late) and later-sown short-season (early) maturity types, respectively.
Publisher: MDPI AG
Date: 04-2021
DOI: 10.3390/LAND10040364
Abstract: Agricultural land-use change is a dynamic process that varies as a function of social, economic and environmental factors spanning from the local to the global scale. The cumulative regional impacts of these factors on land use adoption decisions by farmers are neither well accounted for nor reflected in agricultural land use planning. We present an innovative spatially explicit agent-based modelling approach (Crop GIS-ABM) that accounts for factors involved in farmer decision making on new irrigation adoption to enable land-use predictions and exploration. The model was designed using a participatory approach, capturing stakeholder insights in a conceptual model of farmer decisions. We demonstrate a case study of the factors influencing the uptake of new irrigation infrastructure and land use in Tasmania, Australia. The model demonstrates how irrigated land-use expansion promotes the diffusion of alternative crops in the region, as well as how coupled social, biophysical and environmental conditions play an important role in crop selection. Our study shows that agricultural land use reflected the evolution of multiple simultaneous interacting biophysical and socio-economic drivers, including soil and climate type, crop and commodity prices, and the accumulated effects of interactive decisions of farmers.
Publisher: CSIRO Publishing
Date: 2017
DOI: 10.1071/CP16394
Abstract: Extreme climatic events such as heat waves, extreme rainfall and prolonged dry periods are a significant challenge to the productivity and profitability of dairy systems. Despite projections of more frequent extreme events, increasing temperatures and reduced precipitation, studies on the impact of these extreme climatic events on pasture-based dairy systems remain uncommon. The Intergovernmental Panel on Climate Change has estimated Australia to be one of the most negatively impacted regions with additional studies estimating Australian production losses of around 16% in the agricultural sector and 9–19% between the present and 2050 in the south-eastern dairy regions of Australia due to climate change. Here we review the literature on the impact of climate change on pasture-based dairy systems with particular focus on extreme climatic events. We provide an insight into current methods for assessing and quantifying heat stress highlighting the impacts on pastures and animals including the associated potential productivity losses and conclude by outlining potential adaptation strategies for improving the resilience of the whole-farm systems to climate change. Adapting milking routines, calving systems and the introduction of heat stress tolerant dairy cow breeds are some proposed strategies. Changes in pasture production would also include alternative pasture species better adapted to climate extremes such as heat waves and prolonged periods of water deficit. In order to develop effective adaptation strategies we also need to focus on issues such as water availability, animal health and associated energy costs.
Publisher: MDPI AG
Date: 19-10-2022
DOI: 10.3390/SOILSYSTEMS6040079
Abstract: Many plant species adapted to semi-arid environments are grown in the Sahelian region in northern Africa. One such species is Acacia seyal (Delile), a multipurpose leguminous tree grown in various agroecological zones, including saline soils. These challenging arid and semi-arid environments harbor a ersity of arbuscular mycorrhizal fungi (AMF) communities that can develop symbiotic associations with plants to improve their hydromineral nutrition. This study compared the effects of native AMF communities isolated from semi-arid sites (high, moderate, and low salinity zones Ndiafate, Ngane, and Bambey, respectively) and the AMF Rhizoglomus aggregatum on the development and phosphate nutrition of A. seyal seedlings subject to three salinity treatments (0, 340, and 680 mM). Plant height, dry matter weight of the shoots and roots, and phosphorus uptake from the soil were measured. Plants inoculated with AMF native species from each site that were provided with up to 340 mM of NaCl had greater shoot height than plants grown under 680 mM salinity. At NaCl concentrations above 340 mM, shoot and root development of A. seyal seedlings diminished. However, dry matter production of shoots (7%) and roots (15%) improved following AMF inoculation compared with the control (respectively 0.020 and 0.07 g for shoots and roots). When inoculated with AMF isolates from the high salinity zone (Ndiafate), phosphate content/nutrition was increased by 10% around 30 days after inoculation compared with non-inoculated seedlings (2.84 mg/kg of substrate). These results demonstrate that native AMF inoculants are capable of helping plants withstand environmental constraints, especially those exposing plants to harsh climatic conditions. We discuss insights on how AMF influences the interplay between soil phosphorus and perceived salinity that may have implications for broader relationships between plants and symbiotic fungi.
Publisher: Centro Internacional de Agricultura Tropical
Date: 03-09-2019
Abstract: Keynote paper presented at the International Leucaena Conference, 1‒3 November 2018, Brisbane, Queensland, Australia.The perennial legume leucaena (Leucaena leucocephala) is grown across the subtropics for a variety of purposes including livestock fodder. Livestock in Australia emit a significant proportion of the methane produced by the agriculture sector and there is increasing pressure to decrease emissions from beef cattle production systems. In addition to direct productivity gains for livestock, leucaena has been shown to lower enteric methane production, suggesting an opportunity for emissions mitigation and Commonwealth Emissions Reduction Fund (ERF) methodology development, where leucaena browse is adopted for high value beef production. Determining the proportion of leucaena in the diet may be one of the more challenging aspects in attributing mitigation. Current enteric emission relationships for cattle consuming mixed grass-leucaena diets are based on intensive respiration chamber work. Herd-scale methane flux has also been determined using open path laser methodologies and may be used to validate an on-farm herd-scale methodology for leucaena feeding systems. The methodology should also address increased potential for soil organic carbon storage by leucaena grazing systems, and changes in nitrous oxide production. This paper outlines the background, justification, eligibility requirements and potential gaps in research for an emissions quantification protocol that will lead to the adoption of a leucaena methodology by the Australian beef industry. Development of a methodology would be supported by research conducted in Australia.
Publisher: Wiley
Date: 20-01-2014
DOI: 10.1111/GCB.12381
Abstract: Global climate change is predicted to increase temperatures, alter geographical patterns of rainfall and increase the frequency of extreme climatic events. Such changes are likely to alter the timing and magnitude of drought stresses experienced by crops. This study used new developments in the classification of crop water stress to first characterize the typology and frequency of drought-stress patterns experienced by European maize crops and their associated distributions of grain yield, and second determine the influence of the breeding traits anthesis-silking synchrony, maturity and kernel number on yield in different drought-stress scenarios, under current and future climates. Under historical conditions, a low-stress scenario occurred most frequently (ca. 40%), and three other stress types exposing crops to late-season stresses each occurred in ca. 20% of cases. A key revelation shown was that the four patterns will also be the most dominant stress patterns under 2050 conditions. Future frequencies of low drought stress were reduced by ca. 15%, and those of severe water deficit during grain filling increased from 18% to 25%. Despite this, effects of elevated CO2 on crop growth moderated detrimental effects of climate change on yield. Increasing anthesis-silking synchrony had the greatest effect on yield in low drought-stress seasonal patterns, whereas earlier maturity had the greatest effect in crops exposed to severe early-terminal drought stress. Segregating drought-stress patterns into key groups allowed greater insight into the effects of trait perturbation on crop yield under different weather conditions. We demonstrate that for crops exposed to the same drought-stress pattern, trait perturbation under current climates will have a similar impact on yield as that expected in future, even though the frequencies of severe drought stress will increase in future. These results have important ramifications for breeding of maize and have implications for studies examining genetic and physiological crop responses to environmental stresses.
Publisher: Elsevier BV
Date: 2007
Publisher: Elsevier BV
Date: 09-2020
Publisher: Public Library of Science (PLoS)
Date: 17-07-2018
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/AN14421
Abstract: Livestock greenhouse gas (GHG) emissions form the largest proportion of emissions from agriculture. Here we seek intervention strategies for sustainably intensifying the productivity of prime lamb enterprises without increasing net farm emissions. We apply a biophysical model and an emissions calculator to determine the implications of several interventions to a prime lamb farm in south-eastern Australia. We examine the effects of lamb liveweight or age at sale, weaning rate, maiden ewe joining age, genetic feed-use efficiency, supplementary grain feeding according to green pasture availability, soil fertility and botanical composition. For each intervention, stocking rates were optimised to the lesser of a minimum ground cover threshold or a maximum supplementary grain feeding threshold. Total animal production of the baseline farm was 478 kg clean fleece weight plus liveweight (CFW+LWT)/ha.annum and ranged from 166 to 609 kg CFW+LWT/ha.annum for interventions that replaced existing pastures with annual ryegrass or increased soil fertility respectively. Annual GHG emissions intensity of the baseline farm was 8.7 kg CO2-e/kg CFW+LWT and varied between 7.7 and 9.2 kg CO2-e/kg CFW+LWT for interventions that reduced maiden ewe joining age or increased sale liveweight, respectively. Stocking rate primarily governed total animal production, and in many cases production drove emissions, so interventions that increased production did not always reduce emissions intensity. Indeed, replacing existing perennial ryegrass/subterranean clover mixed pastures with perennial legume swards caused large reductions in both production and emissions, and interventions that increased soil fertility via phosphate addition caused large increases in production and emissions as a consequence, both strategies had little effect on emissions intensity. Implementing several beneficial interventions simultaneously further increased production and reduced emissions intensity relative to implementing in idual interventions alone. Baseline production increased by 61% by increasing soil fertility, improving feed-use efficiency and reducing the joining age of maiden ewes, while baseline emissions intensity was reduced by 17% by improving feed use efficiency, reducing the joining age of maiden ewes and supplementary grain feeding. We demonstrate that imposing several strategies on existing sheep farming systems simultaneously is more conducive to sustainable agricultural intensification than is imposing any single intervention alone, provided in idual strategies were beneficial in their own right. The best strategies for both sustainably increasing production and reducing emissions intensity are those that decouple the linkage between production and emissions such as interventions that shift the balance of the flock away from adults and towards juveniles while holding average annual stocking rates constant.
Publisher: CSIRO Publishing
Date: 2013
DOI: 10.1071/CP12358
Abstract: Grazed pastures in south-eastern Australia are typically based on temperate (C3) species, such as perennial ryegrass (Lolium perenne). With predictions of warming to occur in this region, there has been growing interest in the performance of more heat-tolerant and deep-rooted subtropical (C4) pasture grasses, such as kikuyu (Pennisetum clandestinum). This study used an existing pasture model to estimate the production of kikuyu compared with the commonly used perennial ryegrass at seven sites in south-eastern Australia, using an historical baseline climate scenario between 1971 and 2010, and the daily temperature of the baseline scenario adjusted by +1, +2, and +3°C to represent potential warming in the future. The seven sites were chosen to represent the range of climatic zones and soil types in the region. First, the model predictions of monthly kikuyu dry matter (DM) production were validated with measured data at Taree, Camden, and Bega, with results showing good agreement. Second, pasture production (t DM/ha), metabolisable energy (ME, MJ/kg DM) content, and ME yield (GJ/ha) were predicted using the baseline and warmer climate scenarios. The study was based on 56 simulations of the factorial arrangement of seven sites × four temperature scenarios × two pastures. The month and annual ME yield of a kikuyu–subterranean clover (Trifolium subterraneum) pasture and a perennial ryegrass–subterranean clover pasture were compared. This study showed that in summer-dominant rainfall locations, where the average maximum temperature is °C, kikuyu was a more productive pasture species than perennial ryegrass. In winter-dominant rainfall locations during the warmer months of December–March, kikuyu can provide a useful source of ME when perennial ryegrass is less productive. With warming of up to 3°C at the winter-dominant rainfall sites, the average ME yield per year of kikuyu was predicted to surpass that of perennial ryegrass, but inter-annual variation in kikuyu production was higher. The nutritive value, seasonal distribution of growth, total annual production, and its variability are all important considerations for producers when selecting pasture species.
Publisher: Elsevier BV
Date: 02-2021
Publisher: CSIRO Publishing
Date: 2018
DOI: 10.1071/AN15632
Abstract: Recognition is increasingly given to the need of improving agricultural production and efficiency to meet growing global food demand, while minimising environmental impacts. Livestock forms an important component of global food production and is a significant contributor to anthropogenic greenhouse-gas (GHG) emissions. As such, livestock production systems (LPS) are coming under increasing pressure to lower their emissions. In developed countries, LPS have been gradually reducing their emissions per unit of product (emissions intensity EI) over time through improvements in production efficiency. However, the global challenge of reducing net emissions (NE) from livestock requires that the rate of decline in EI surpasses the productivity increases required to satisfy global food demand. Mechanistic and dynamic whole farm-system models can be used to estimate farm-gate GHG emissions and to quantify the likely changes in farm NE, EI, farm productivity and farm profitability as a result of applying various mitigation strategies. Such models are also used to understand the complex interactions at the farm-system level and to account for how component mitigation strategies perform within the complexity of these interactions, which is often overlooked when GHG mitigation research is performed only at the component level. The results of such analyses can be used in extension activities and to encourage adoption, increase awareness and in assisting policy makers. The present paper reviews how whole farm-system modelling has been used to assess GHG mitigation strategies, and the importance of understanding metrics and allocation approaches when assessing GHG emissions from LPS.
Publisher: Oxford University Press (OUP)
Date: 12-12-2021
DOI: 10.1093/INSILICOPLANTS/DIAA013
Abstract: Seasonal pasture monitoring can increase the efficiency of pasture utilization in livestock grazing enterprises. However, manual monitoring of pasture over large areas is often infeasible due to time and financial constraints. Here, we monitor changes in botanical composition in Tasmania, Australia, through application of supervised learning using satellite imagery (Sentinel-2). In the field, we measured ground cover and botanical composition over a 12-month period to develop a supervised classification approach used to identify pasture classes. Across seasons and paddocks, the approach predicted pasture classes with 75–81 % accuracy. Botanical composition varied seasonally in response to biophysical factors (primarily climate) and grazing behaviour, with seasonal highs in spring and troughs in autumn. Overall, we demonstrated that 10-m multispectral imagery can be reliably used to distinguish between pasture species as well as seasonal changes in botanical composition. Our results suggest that farmers and land managers should aim to quantify within-paddock variability rather than paddock average cover, because the extent and duration of very low ground cover puts the paddock/field at risk of adverse grazing outcomes, such as soil erosion and loss of pasture biomass, soil carbon and bio ersity. Our results indicate that satellite imagery can be used to support grazing management decisions for the benefit of pasture production and the improvement of environmental sustainability.
Publisher: CSIRO Publishing
Date: 2015
DOI: 10.1071/CPV66N4_FO
Publisher: Cold Spring Harbor Laboratory
Date: 07-01-2021
DOI: 10.1101/2021.01.04.425314
Abstract: We introduce the AusTraits database - a compilation of measurements of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 375 traits across 29230 taxa from field c aigns, published literature, taxonomic monographs, and in idual taxa descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological parameters (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised in idual-, species- and genus-level observations coupled to, where available, contextual information on site properties. This data descriptor provides information on version 2.1.0 of AusTraits which contains data for 937243 trait-by-taxa combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data to increase our collective understanding of the Australian flora.
Publisher: MDPI AG
Date: 03-01-2023
DOI: 10.3390/LAND12010164
Abstract: Drought impacts on food security, land degradation and rates of bio ersity loss. Here, we aimed to investigate selenium nanoparticles (Se NPs) influenced plant resilience to drought using the morphological, physiological, and essential oil (EO) quantity and quality of basil (Ocimum basilicum L.) as drought proxies. Treatments included irrigation at 100% field capacity (FC100) as no stress, 80% FC as moderate water stress (FC80) and 60% FC as severe water stress (FC60), together with application of Se NPs at either 0 mg L−1 (control), 50 mg L−1, or 100 mg L−1. The highest (257 g m−2) and lowest (185 g m−2) dry matter yields were achieved in nil-stress and severe-water-stress conditions, respectively. Dry matter yields decreased by 15% and 28% under moderate and severe water stress, respectively. Applying Se NPs enhanced the dry matter yields by 14% and 13% for the 50 and 100 mg L−1 treatments, respectively. The greatest EO content (1.0%) and EO yield (1.9 g m−2) were observed under severe water stress. Applying Se NPs of 50 and 100 mg L−1 enhanced the essential oil content by 33% and 36% and the essential oil yield by 52% and 53%, respectively. We identified 21 constituents in the EO, with primary constituents being methyl chavicol (40%–44%), linalool (38–42%), and 1,8-cineole (5–6%). The greatest methyl chavicol and linalool concentrations were obtained in FC80 with 50 mg L−1 Se NPs. The highest proline (17 µg g−1 fresh weight) and soluble sugar content (6 mg g−1 fresh weight) were obtained under severe water stress (FC60) for the 50 mg L−1 Se NP treatment. Our results demonstrate that low-concentration Se NPs increase plant tolerance and improve the EO quantity and quality of basil under drought stress.
Publisher: Wiley
Date: 29-08-2021
DOI: 10.1111/GCB.15816
Abstract: Livestock have long been integral to food production systems, often not by choice but by need. While our knowledge of livestock greenhouse gas (GHG) emissions mitigation has evolved, the prevailing focus has been—somewhat myopically—on technology applications associated with mitigation. Here, we (1) examine the global distribution of livestock GHG emissions, (2) explore social, economic and environmental co‐benefits and trade‐offs associated with mitigation interventions and (3) critique approaches for quantifying GHG emissions. This review uncovered many insights. First, while GHG emissions from ruminant livestock are greatest in low‐ and middle‐income countries (LMIC globally, 66% of emissions are produced by Latin America and the Caribbean, East and southeast Asia and south Asia), the majority of mitigation strategies are designed for developed countries. This serious concern is heightened by the fact that 80% of growth in global meat production over the next decade will occur in LMIC. Second, few studies concurrently assess social, economic and environmental aspects of mitigation. Of the 54 interventions reviewed, only 16 had triple‐bottom line benefit with medium–high mitigation potential. Third, while efforts designed to stimulate the adoption of strategies allowing both emissions reduction (ER) and carbon sequestration (CS) would achieve the greatest net emissions mitigation, CS measures have greater potential mitigation and co‐benefits. The scientific community must shift attention away from the prevailing myopic lens on carbon, towards more holistic, systems‐based, multi‐metric approaches that carefully consider the raison d'être for livestock systems. Consequential life cycle assessments and systems‐aligned ‘socio‐economic planetary boundaries’ offer useful starting points that may uncover leverage points and cross‐scale emergent properties. The derivation of harmonized, globally reconciled sustainability metrics requires iterative dialogue between stakeholders at all levels. Greater emphasis on the simultaneous characterization of multiple sustainability dimensions would help avoid situations where progress made in one area causes maladaptive outcomes in other areas.
Publisher: Elsevier BV
Date: 2016
Publisher: MDPI AG
Date: 16-01-2023
Abstract: Here we document physiological and molecular attributes of three wheat cultivars (ZM9023, YM158 and FM1228) under low light intensity with advanced technologies, including non-standard quantitative technology and quantitative proteomics technology. We found lower dry matter accumulation of YM158 compared with ZM 9023 and FM1228 under low light intensities due to up-regulation of photosynthetic parameters electron transport rate (ETR), Y(II), Fv/Fm, Chl (a + b) of YM158 and down-regulation of Chl a/b. ETR, Y(II) and Fv/Fm significantly decreased between ZM9023 and FM1228. The ETR between PSII and PSI of YM158 increased, while light use efficiency (LUE) of ZM9023 and FM1228 decreased. We found that YM158 had greater propensity to adapt to low light compared with ZM9023, as the former was able to increase photochemical electron transfer rate, enhance photosystem activity, and increase the light energy under low light. This meant that the YM158 flag leaf has stronger regulatory mechanism under low light environment. Through proteomic analysis, we found LHC protein (LHCB1, LHCB4, LHCA2, LHCA3) for YH158 was significantly up-regulated, while the PSII subunit protein of FM1228 and ZM9023 b559 subunit protein were down-regulated. We also documented enhanced light use efficiency (LUE) due to higher light capture pigment protein complex (LHC), photosystem II (PSII), PSI and cytochrome B6F-related proteins, with dry matter accumulation being positively correlated with Fv/Fm, ETR, and ΦPS(II), and negatively correlated with initial fluorescence F0. We suggest that Fv/Fm, ETR, and ΦPS(II) could be considered in shade tolerance screening to facilitate wheat breeding.
Publisher: MDPI AG
Date: 28-08-2023
Abstract: Superior yields of super hybrid rice have demonstrably contributed to contemporary food security. Despite this, the extent to which intensive nitrogen fertilizer requirements of such crops have impacted on soil health and microbial communities primarily remains unchartered territory, evoking questions of sustainability. Here, we examine how four management treatments (zero fertilizer, CK farm practice, FP high-yield and high-efficiency, HYHE and super-high-yield management, SHY) influenced the grain yields, soil bio ersity and community strata underpinning soil health of an elite super hybrid rice variety (Y-liangyou 900). We show that SHY treatments increased yields, altered soil physicochemical properties, and fostered greater bio ersity and soil bacteria and fungi abundance, while FP, HYHE and SHY treatments transformed community bacteria and fungi strata. Environmental regulators of bacterial and fungal communities differed widely, with bacterial communities most closely associated with soil organic carbon (SOC) and NH4+-N, and with fungal communities more related to available phosphorus. We show that alpha ersity of bacteria and fungi and community composition of fungi were positively correlated with yield, but bacterial community composition was negatively correlated with yield. Our work clearly exemplifies the nexus between appropriate farm and landscape management in enabling soil health and driving consistently high yields, of which both are required for sustainable food security.
Publisher: Wiley
Date: 08-08-2020
DOI: 10.1002/FES3.238
Publisher: MDPI AG
Date: 20-10-2022
DOI: 10.20944/PREPRINTS202210.0297.V1
Abstract: With global warming, arable land in boreal regions is tending to expand into high latitude regions in the northern hemisphere. This entails certain risks such that inappropriate management could result in previously stable carbon sinks becoming sources. Agroecological models are an important tool for assessing the sustainability of long-term management, yet applications of such models in boreal zones are scarce. We collated eddy-covariance, soil climate and biomass data to evaluate the simulation of GHG emissions from grassland in eastern Finland using the process-based model DNDC. We simulated gross primary production (GPP), net ecosystem exchange (NEE) and ecosystem respiration (Reco) with fair performance. Soil climate, soil temperature and soil moisture at 5 cm were excellent, and soil moisture at 20 cm was good. However, the model overestimated NEE and Reco following crop termination and tillage events. These results indicate that DNDC can satisfactorily simulate GHG fluxes in a boreal grassland setting, but further work is needed, particularly in simulated second biomass cuts, the (& cm) soil layers and model response to management transitions between crop types, cultivation, and land use change.
Publisher: MDPI AG
Date: 24-03-2023
DOI: 10.3390/SU15075694
Abstract: Drought stress restricts the growth of okra (Abelmoschus esculentus L.) by disrupting its biochemical and physiological functions. The current study was conducted to evaluate the role of selenium (0, 1, 2, and 3 mg Se L−1 as a foliar application) in improving okra tolerance to drought (control (100% field capacity-FC), mild stress (70% FC), and severe stress (35% FC)) imposed 30 days after sowing (DAS). Drought (severe) markedly decreased chlorophyll (32.21%) and carotenoid (39.6%) contents but increased anthocyanin (40%), proline (46.8%), peroxidase (POD by 12.5%), ascorbate peroxidase (APX by 11.9%), and catalase (CAT by 14%) activities. Overall, Se application significantly alleviated drought stress-related biochemical disturbances in okra. Mainly, 3 mg Se L−1 significantly increased chlorophyll (21%) as well as anthocyanin (15.14%), proline (18.16%), and antioxidant activities both under drought and control conditions. Selenium played a beneficial role in reducing damage caused by oxidative stress, enhancing chlorophyll and antioxidants contents, and improved plant tolerance to drought stress. Therefore, crops including okra especially, must be supplemented with 3 mg L−1 foliar Se for obtaining optimum yield in arid and semiarid drought-affected areas.
Start Date: 2013
End Date: 2013
Funder: Sense-T within University of Tasmania
View Funded ActivityStart Date: 2015
End Date: 2018
Funder: Department of Primary Industries, Parks, Water & Environment
View Funded ActivityStart Date: 2015
End Date: 2016
Funder: University of Tasmania
View Funded ActivityStart Date: 2015
End Date: 2016
Funder: Dairy Australia Limited
View Funded Activity