Diversity of Cicadellidae in agricultural production areas in the Ovens Valley, Northeast Victoria, Australia

There is a paucity of data on the distribution of Cicadellidae (leafhoppers) in Australia. This study quantifies the relative abundance, seasonal activity and diversity of leafhoppers in the Ovens Valley region of north-east Victoria, Australia. Species diversity and abundance was assessed at four field sites in and around the field borders of commercially grown tobacco crops using three sampling techniques (pan trap, sticky trap and sweep net). Over 51 000 leafhopper samples were collected, with 57 species from 11 subfamilies and 19 tribes identified. Greater numbers and diversity of leafhoppers were collected in yellow pan traps. The predominant leafhopper collected was Orosius orientalis (Matsumura). Twenty-three leafhopper species were recorded for the first time in Victoria and eight economically important pest species were recorded. Seasonal activity of selected leafhopper species, covering two sampling seasons, is presented.

Participatory design for technological disruption within the agricultural sector

Agricultural adoption of innovation has traditionally been described as slow to diffuse. This paper therefore describes a case study grounded in PD to address a disruptive technology/system within the livestock industry. Results of the process were positive, as active engagement of stakeholders returned rich data. The contribution of the work is also presented as grounds for further design research in the livestock industry.

How can soil monitoring networks be used to improve predictions of organic carbon pool dynamics and CO2 fluxes in agricultural soils?

Abstract As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach). Keywords Soil monitoring networks - Soil organic carbon - Modeling - Sampling design

Measuring and decomposing changes in agricultural productivity, nitrogen use efficiency and cumulative exergy efficiency: Application to OECD agriculture

This paper uses an aggregate quantity space to decompose the temporal changes in nitrogen use efficiency and cumulative exergy use efficiency into changes of Moorsteen–Bjurek (MB) Total Factor Productivity (TFP) changes and changes in the aggregate nitrogen and cumulative exergy contents. Changes in productivity can be broken into technical change and changes in various efficiency measures such as technical efficiency, scale efficiency and residual mix efficiency. Changes in the aggregate nitrogen and cumulative exergy contents can be driven by changes in the quality of inputs and outputs and changes in the mixes of inputs and outputs. Also with cumulative exergy content analysis, changes in the efficiency in input production can increase or decrease the cumulative exergy transformity of agricultural production. The empirical study in 30 member countries of the Organisation for Economic Co-operation Development from 1990 to 2003 yielded some important findings. The production technology progressed but there were reductions in technical efficiency, scale efficiency and residual mix efficiency levels. This result suggests that the production frontier had shifted up but there existed lags in the responses of member countries to the technological change. Given TFP growth, improvements in nutrient use efficiency and cumulative exergy use efficiency were counteracted by reductions in the changes of the aggregate nitrogen contents ratio and aggregate cumulative exergy contents ratio. The empirical results also confirmed that different combinations of inputs and outputs as well as the quality of inputs and outputs could have more influence on the growth of nutrient and cumulative exergy use efficiency than factors that had driven productivity change. Keywords: Nutrient use efficiency; Cumulative exergy use efficiency; Thermodynamic efficiency change; Productivity growth; OECD agriculture; Sustainability

Measuring and monitoring soil organic carbon stocks in agricultural lands for climate mitigation

Policies that encourage greenhouse-gas emitters to mitigate emissions through terrestrial carbon (C) offsets – C sequestration in soils or biomass – will promote practices that reduce erosion and build soil fertility, while fostering adaptation to climate change, agricultural development, and rehabilitation of degraded soils. However none of these benefits will be possible until changes in C stocks can be documented accurately and cost-effectively. This is particularly challenging when dealing with changes in soil organic C (SOC) stocks. Precise methods for measuring C in soil samples are well established, but spatial variability in the factors that determine SOC stocks makes it difficult to document change. Widespread interest in the benefits of SOC sequestration has brought this issue to the fore in the development of US and international climate policy. Here, we review the challenges to documenting changes in SOC stocks, how policy decisions influence offset documentation requirements, and the benefits and drawbacks of different sampling strategies and extrapolation methods.

A Bayesian analysis of an agricultural field trial with three spatial dimensions

Modern technology now has the ability to generate large datasets over space and time. Such data typically exhibit high autocorrelations over all dimensions. The field trial data motivating the methods of this paper were collected to examine the behaviour of traditional cropping and to determine a cropping system which could maximise water use for grain production while minimising leakage below the crop root zone. They consist of moisture measurements made at 15 depths across 3 rows and 18 columns, in the lattice framework of an agricultural field. Bayesian conditional autoregressive (CAR) models are used to account for local site correlations. Conditional autoregressive models have not been widely used in analyses of agricultural data. This paper serves to illustrate the usefulness of these models in this field, along with the ease of implementation in WinBUGS, a freely available software package. The innovation is the fitting of separate conditional autoregressive models for each depth layer, the ‘layered CAR model’, while simultaneously estimating depth profile functions for each site treatment. Modelling interest also lay in how best to model the treatment effect depth profiles, and in the choice of neighbourhood structure for the spatial autocorrelation model. The favoured model fitted the treatment effects as splines over depth, and treated depth, the basis for the regression model, as measured with error, while fitting CAR neighbourhood models by depth layer. It is hierarchical, with separate onditional autoregressive spatial variance components at each depth, and the fixed terms which involve an errors-in-measurement model treat depth errors as interval-censored measurement error. The Bayesian framework permits transparent specification and easy comparison of the various complex models compared.

Mapping of shallow coastal groundwaters, their hydrology and environmental geochemistry : Pumicestone catchment, Southeast Queensland

Blooms of the toxic cyanobacterium majuscula Lyngbya in the coastal waters of southeast Queensland have caused adverse impacts on both environmental health and human health, and on local economies such as fishing and tourism. A number of studies have confirmed that the main limiting nutrients (“nutrients of concern”) that contribute to these blooms area Fe, DOC, N, P and also pH. This study is conducted to establish the distribution of these parameters in a typical southeast Queensland coastal setting. The study maps the geochemistry of shallow groundwater in the mainland Pumicestone catchment with an emphasis on the nutrients of concern to understand how these nutrients relate to aquifer materials, landuse and anthropogenic activities. The results of the study form a GIS information layer which will be incorporated into a larger GIS model being produced by Queensland Department of Environment and Resource Management (DERM) to support landuse management to avoid/minimize blooms of Lyngbya in Moreton Bay, southeast Queensland, and other similar settings. A total of 38 boreholes were established in the mainland Pumicestone region and four sampling rounds of groundwater carried out in both dry and wet conditions. These groundwater samples were measured in the field for physico-chemical parameters, and in the laboratory analyses for the nutrients of concern, and other major and minor ions. Aquifer materials were confirmed using the Geological Survey of Queensland digital geology map, and geomaterials were assigned to seven categories which are A (sands), B (silts, sandy silts), C (estuarine mud, silts), D (humid soils), E (alluvium), F (sandstone) and G (other bedrock). The results of the water chemistry were examined by use of the software package AquaChem/AqQA, and divided into six groundwater groups, based on groundwater chemical types and location of boreholes. The type of aquifer material and location, and proximity to waterways was found to be important because they affected physico-chemical properties and concentrations of nutrients of concern and dissolved ions. The analytical results showed that iron concentrations of shallow groundwaters were high due to acid sulfate soils, and also mud and silt, but were lower in sand materials. DOC concentrations of these shallow groundwaters in the sand material were high probably due to rapid infiltration. In addition, DOC concentrations in some boreholes were high because they were installed in organic rich wetlands. The pH values of boreholes were from acidic to near neutral; some boreholes with pH values were low (< 4), showing acid sulfate soils in these boreholes. Concentrations of total nitrogen and total phosphorus of groundwaters were generally low, and the main causes of elevated concentrations of total nitrogen and total phosphorus are largely due to animal and human wastes and tend to be found in localized source areas. Comparison of the relative percentage of nitrogen species (NH3/NH4< Org-N, NO3-N and NO2-N) demonstrated that they could be related to sources such as animal waste, residential and agricultural fertilizers, forest and vegetation, mixed residents and farms, and variable setting and vegetation covers. Total concentrations of dissolved ions in sampling round 3 (dry period) were higher than those in sampling round 2 (wet period) due to both evaporation of groundwater in the dry period and the dilution of rainfall in the wet period. This showed that the highest concentrations of nutrients of concern were due to acid sulfate soils, aquifer materials, landuse and anthropogenic activities and were typically in aquifer materials of E (alluvium) and C (estuarine muds) and locations of Burpengary, Caboolture, and Glass Mountain catchments.

Feasibility study for thermal treatment of solid tire wastes in Bangladesh by using pyrolysis technology

In this study on the basis of lab data and available resources in Bangladesh, feasibility study has been carried out for pyrolysis process converting solid tire wastes into pyrolysis oils, solid char and gases. The process considered for detailed analysis was fixed-bed fire-tube heating pyrolysis reactor system. The comparative techno-economic assessment was carried out in US$ for three different sizes plants: medium commercial scale (144 tons/day), small commercial scale (36 tons/day), pilot scale (3.6 tons/day). The assessment showed that medium commercial scale plant was economically feasible, with the lowest unit production cost than small commercial and pilot scale plants for the production of crude pyrolysis oil that could be used as boiler fuel oil and for the production of upgraded liquid-products.

Corporate social and environmental responsibility in relation to the agricultural sector and the food supply chain : a Case Study of Waitrose

Waitrose has a strong commitment to organic farming but also uses products from 'conventional' farms. At the production stage, Waitrose own-label products are fully traceable, GM-free and all suppliers undergo a detailed assessment programme based on current best practice. Crop suppliers to Waitrose operate an authenticity programme to certify that each assignment is GM-free and produce is screened for pesticide residues. Waitrose sources conventional crops grown from 'Integrated Crop Management Systems' (ICMS) using best horticultural practices. The 'Assured Product' scheme regulates all UK produce to ICMS standards and these audits are being extended worldwide. Business is withdrawn from suppliers who fail the audit. In relation to this, Waitrose has increased its Fairtrade range as in its view 'Buying these products provides direct additional benefit to workers in the developing countries where they are produced and assists marginal producers by giving them access to markets they would not otherwise have'. Currently, Waitrose is developing its own sustainable timber assessment criteria. For livestock, protocols are in place to ensure that animals are reared under the 'most natural conditions possible' and free range produce is offered where animals have access to open space although some produce is not from free-range animals. Waitrose also use a 'Hazards Analysis Critical Points' system to identify food safety hazards that occur at any stage from production to point of sale and to ensure that full measures are in place to control them. In addition, mechanisms have been implemented to reduce fuel use and hence reduce CO2 emissions in the transport of products and staff, and to increase the energy use efficiency of refrigeration systems which account for approximately 60% of Waitrose energy use.