Physiological basis of yield variation in response to row spacing and plant density of mungbean grown in subtropical environments

In this study, we investigated the extent and physiological bases of yield variation due to row spacing and plant density configuration in the mungbean Vigna radiata (L.) Wilczek variety “Crystal” grown in different subtropical environments. Field trials were conducted in six production environments; one rain-fed and one irrigated trial each at Biloela and Emerald, and one rain-fed trial each at Hermitage and Kingaroy sites in Queensland, Australia. In each trial, six combinations of spatial arrangement of plants, achieved through two inter-row spacings of 1 m or 0.9 m (wide row), 0.5 m or 0.3 m (narrow row), with three plant densities, 20, 30 and 40 plants/m2, were compared. The narrow row spacing resulted in 22% higher shoot dry matter and 14% more yield compared to the wide rows. The yield advantage of narrow rows ranged from 10% to 36% in the two irrigated and three rain-fed trials. However, yield loss of up to 10% was also recorded from narrow rows at Emerald where the crop suffered severe drought. Neither the effects of plant density, nor the interaction between plant density and row spacing, however, were significant in any trial. The yield advantage of narrow rows was related to 22% more intercepted radiation. In addition, simulations by the Agricultural Production Systems Simulator model, using site-specific agronomy, soil and weather information, suggested that narrow rows had proportionately greater use of soil water through transpiration, compared to evaporation resulting in higher yield per mm of soil water. The long-term simulation of yield probabilities over 123 years for the two row configurations showed that the mungbean crop planted in narrow rows could produce up to 30% higher grain yield compared to wide rows in 95% of the seasons.

Legumes or nitrification inhibitors to reduce N2O emissions from subtropical cereal cropping systems in Oxisols?

The DAYCENT biogeochemical model was used to investigate how the use of fertilizers coated with nitrification inhibitors and the introduction of legumes in the crop rotation can affect subtropical cereal production and N2O emissions. The model was validated using comprehensive multi-seasonal, high-frequency dataset from two field investigations conducted on an Oxisol, which is the most common soil type in subtropical regions. Different N fertilizer rates were tested for each N management strategy and simulated under varying weather conditions. DAYCENT was able to reliably predict soil N dynamics, seasonal N2O emissions and crop production, although some discrepancies were observed in the treatments with low or no added N inputs and in the simulation of daily N2O fluxes. Simulations highlighted that the high clay content and the relatively low C levels of the Oxisol analyzed in this study limit the chances for significant amounts of N to be lost via deep leaching or denitrification. The application of urea coated with a nitrification inhibitor was the most effective strategy to minimize N2O emissions. This strategy however did not increase yields since the nitrification inhibitor did not substantially decrease overall N losses compared to conventional urea. Simulations indicated that replacing part of crop N requirements with N mineralized by legume residues is the most effective strategy to reduce N2O emissions and support cereal productivity. The results of this study show that legumes have significant potential to enhance the sustainable and profitable intensification of subtropical cereal cropping systems in Oxisols.

Comparison of the impact of six heat-load management strategies on thermal responses and milk production of feed-pad and pasture fed dairy cows in a subtropical environment

Exposure to hot environments affects milk yield (MY) and milk composition of pasture and feed-pad fed dairy cows in subtropical regions. This study was undertaken during summer to compare MY and physiology of cows exposed to six heat-load management treatments. Seventy-eight Holstein-Friesian cows were blocked by season of calving, parity, milk yield, BW, and milk protein (%) and milk fat (%) measured in 2 weeks prior to the start of the study. Within blocks, cows were randomly allocated to one of the following treatments: open-sided iron roofed day pen adjacent to dairy (CID) + sprinklers (SP); CID only; non-shaded pen adjacent to dairy + SP (NSD + SP); open-sided shade cloth roofed day pen adjacent to dairy (SCD); NSD + sprinkler (sprinkler on for 45 min at 1100 h if mean respiration rate >80 breaths per minute (NSD + WSP)); open-sided shade cloth roofed structure over feed bunk in paddock + 1 km walk to and from the dairy (SCP + WLK). Sprinklers for CID + SP and NSD + SP cycled 2 min on, 12 min off when ambient temperature >26°C. The highest milk yields were in the CID + SP and CID treatments (23.9 L cow−1 day−1), intermediate for NSD + SP, SCD and SCP + WLK (22.4 L cow−1 day−1), and lowest for NSD + WSP (21.3 L cow−1 day−1) (P < 0.05). The highest (P < 0.05) feed intakes occurred in the CID + SP and CID treatments while intake was lowest (P < 0.05) for NSD + WSP and SCP + WLK. Weather data were collected on site at 10-min intervals, and from these, THI was calculated. Nonlinear regression modelling of MY × THI and heat-load management treatment demonstrated that cows in CID + SP showed no decline in MY out to a THI break point value of 83.2, whereas the pooled MY of the other treatments declined when THI >80.7. A combination of iron roof shade plus water sprinkling throughout the day provided the most effective control of heat load.

Legumes or nitrification inhibitors to reduce {N2O} emissions from subtropical cereal cropping systems in Oxisols?

The DAYCENT biogeochemical model was used to investigate how the use of fertilizers coated with nitrification inhibitors and the introduction of legumes in the crop rotation can affect subtropical cereal production and {N2O} emissions. The model was validated using comprehensive multi-seasonal, high-frequency dataset from two field investigations conducted on an Oxisol, which is the most common soil type in subtropical regions. Different N fertilizer rates were tested for each N management strategy and simulated under varying weather conditions. DAYCENT was able to reliably predict soil N dynamics, seasonal {N2O} emissions and crop production, although some discrepancies were observed in the treatments with low or no added N inputs and in the simulation of daily {N2O} fluxes. Simulations highlighted that the high clay content and the relatively low C levels of the Oxisol analyzed in this study limit the chances for significant amounts of N to be lost via deep leaching or denitrification. The application of urea coated with a nitrification inhibitor was the most effective strategy to minimize {N2O} emissions. This strategy however did not increase yields since the nitrification inhibitor did not substantially decrease overall N losses compared to conventional urea. Simulations indicated that replacing part of crop N requirements with N mineralized by legume residues is the most effective strategy to reduce {N2O} emissions and support cereal productivity. The results of this study show that legumes have significant potential to enhance the sustainable and profitable intensification of subtropical cereal cropping systems in Oxisols.

Legume pastures can reduce N2O emissions intensity in subtropical cereal cropping systems

Alternative sources of N are required to bolster subtropical cereal production without increasing N2O emissions from these agro-ecosystems. The reintroduction of legumes in cereal cropping systems is a possible strategy to reduce synthetic N inputs but elevated N2O losses have sometimes been observed after the incorporation of legume residues. However, the magnitude of these losses is highly dependent on local conditions and very little data are available for subtropical regions. The aim of this study was to assess whether, under subtropical conditions, the N mineralised from legume residues can substantially decrease the synthetic N input required by the subsequent cereal crop and reduce overall N2O emissions during the cereal cropping phase. Using a fully automated measuring system, N2O emissions were monitored in a cereal crop (sorghum) following a legume pasture and compared to the same crop in rotation with a grass pasture. Each crop rotation included a nil and a fertilised treatment to assess the N availability of the residues. The incorporation of legumes provided enough readily available N to effectively support crop development but the low labile C left by these residues is likely to have limited denitrification and therefore N2O emissions. As a result, N2O emissions intensities (kg N2O-N yield−1 ha−1) were considerably lower in the legume histories than in the grass. Overall, these findings indicate that the C supplied by the crop residue can be more important than the soil NO3− content in stimulating denitrification and that introducing a legume pasture in a subtropical cereal cropping system is a sustainable practice from both environmental and agronomic perspectives.

Evaluation of TRMM PR Sampling Error Over a Subtropical Basin Using Bootstrap Technique

Quantitative use of satellite-derived rainfall products for various scientific applications often requires them to be accompanied with an error estimate. Rainfall estimates inferred from low earth orbiting satellites like the Tropical Rainfall Measuring Mission (TRMM) will be subjected to sampling errors of nonnegligible proportions owing to the narrow swath of satellite sensors coupled with a lack of continuous coverage due to infrequent satellite visits. The authors investigate sampling uncertainty of seasonal rainfall estimates from the active sensor of TRMM, namely, Precipitation Radar (PR), based on 11 years of PR 2A25 data product over the Indian subcontinent. In this paper, a statistical bootstrap technique is investigated to estimate the relative sampling errors using the PR data themselves. Results verify power law scaling characteristics of relative sampling errors with respect to space-time scale of measurement. Sampling uncertainty estimates for mean seasonal rainfall were found to exhibit seasonal variations. To give a practical example of the implications of the bootstrap technique, PR relative sampling errors over a subtropical river basin of Mahanadi, India, are examined. Results reveal that the bootstrap technique incurs relative sampling errors < 33% (for the 2 degrees grid), < 36% (for the 1 degrees grid), < 45% (for the 0.5 degrees grid), and < 57% (for the 0.25 degrees grid). With respect to rainfall type, overall sampling uncertainty was found to be dominated by sampling uncertainty due to stratiform rainfall over the basin. The study compares resulting error estimates to those obtained from latin hypercube sampling. Based on this study, the authors conclude that the bootstrap approach can be successfully used for ascertaining relative sampling errors offered by TRMM-like satellites over gauged or ungauged basins lacking in situ validation data. This technique has wider implications for decision making before incorporating microwave orbital data products in basin-scale hydrologic modeling.

Evaluation of Precipitation Retrievals From Orbital Data Products of TRMM Over a Subtropical Basin in India

The spatial error structure of daily precipitation derived from the latest version 7 (v7) tropical rainfall measuring mission (TRMM) level 2 data products are studied through comparison with the Asian precipitation highly resolved observational data integration toward evaluation of the water resources (APHRODITE) data over a subtropical region of the Indian subcontinent for the seasonal rainfall over 6 years from June 2002 to September 2007. The data products examined include v7 data from the TRMM radiometer Microwave Imager (TMI) and radar precipitation radar (PR), namely, 2A12, 2A25, and 2B31 (combined data from PR and TMI). The spatial distribution of uncertainty from these data products were quantified based on performance metrics derived from the contingency table. For the seasonal daily precipitation over a subtropical basin in India, the data product of 2A12 showed greater skill in detecting and quantifying the volume of rainfall when compared with the 2A25 and 2B31 data products. Error characterization using various error models revealed that random errors from multiplicative error models were homoscedastic and that they better represented rainfall estimates from 2A12 algorithm. Error decomposition techniques performed to disentangle systematic and random errors verify that the multiplicative error model representing rainfall from 2A12 algorithm successfully estimated a greater percentage of systematic error than 2A25 or 2B31 algorithms. Results verify that although the radiometer derived 2A12 rainfall data is known to suffer from many sources of uncertainties, spatial analysis over the case study region of India testifies that the 2A12 rainfall estimates are in a very good agreement with the reference estimates for the data period considered.

Coastal Pelagic Fishes (Report of Working Group 3); Subarctic Gyre (Report of Working Group 6)

This is a report of PICES Working Group 3 (Coastal Pelagic Fishes) for 1993 and the first Annual Report of the Subarctic Gyre Working Group (WG-6). (PDF contains 131 pages)

Simulations and mechanisms of subtropical low-cloud response to climate change

This thesis focuses on improving the simulation skills and the theoretical understanding of the subtropical low cloud response to climate change.

First, an energetically consistent forcing framework is designed and implemented for the large eddy simulation (LES) of the low-cloud response to climate change. The three representative current-day subtropical low cloud regimes of cumulus (Cu), cumulus-over-stratocumulus, and stratocumulus (Sc) are all well simulated with this framework, and results are comparable to the conventional fixed-SST approach. However, the cumulus response to climate warming subject to energetic constraints differs significantly from the conventional approach with fixed SST. Under the energetic constraint, the subtropics warm less than the tropics, since longwave (LW) cooling is more efficient with the drier subtropical free troposphere. The surface latent heat flux (LHF) also increases only weakly subject to the surface energetic constraint. Both factors contribute to an increased estimated inversion strength (EIS), and decreased inversion height. The decreased Cu-depth contributes to a decrease of liquid water path (LWP) and weak positive cloud feedback. The conventional fixed-SST approach instead simulates a strong increase in LHF and deepening of the Cu layer, leading to a weakly negative cloud feedback. This illustrates the importance of energetic constraints to the simulation and understanding of the sign and magnitude of low-cloud feedback.

Second, an extended eddy-diffusivity mass-flux (EDMF) closure for the unified representation of sub-grid scale (SGS) turbulence and convection processes in general circulation models (GCM) is presented. The inclusion of prognostic terms and the elimination of the infinitesimal updraft fraction assumption makes it more flexible for implementation in models across different scales. This framework can be consistently extended to formulate multiple updrafts and downdrafts, as well as variances and covariances. It has been verified with LES in different boundary layer regimes in the current climate, and further development and implementation of this closure may help to improve our simulation skills and understanding of low-cloud feedback through GCMs.