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Responsiveness of demand for structural pine to changes in timber and steel prices: A study using the FWPA softwood data series
No full textOverview \r\n This technical report estimates the responsiveness of demand for structural pine to changes in timber and steel prices. Measures of demand responsiveness can provide valuable insights into the potential implications of changes in policy or market settings on volumes and prices received by producers. The analysis focuses on estimating short-term price elasticities of demand--a formal measure of the sensitivity of demand--to changes in prices in the same quarter or recent past. \r\n\r\n Key Issues \r\n The estimates in this report suggest that the importance of timber and steel prices on the quantity of structural timber demanded in the short-run is limited. However, the volume of residential construction activity was found to have a substantial effect for demand of domestically produced structural pine products. In particular, new house commencements explain a great deal of the quarter-on-quarter changes in the quantity of domestic structural pine sales. This confirms the common assertion by industry that house commencements are the primary driver for structural timber demand within Australia. \r\n\r\n Looking forward, changes in consumer preferences, socio-demographic trends and building regulations will likely play a much greater role in the choice of building materials used in housing construction compared with timber and steel prices. Trends suggest consumers are placing more weight on the environmental benefits of structural materials. Changing architectural styles will change the material requirements for a standard home. A global trend towards higher-density living will likely promote a shift toward multi-unit buildings, with recent changes to the National Construction Code opening the way for increased timber use in the midrise construction market, leading to greater timber use in multi-level buildings. \r\nResponsiveness of demand for structural pine to changes in timber and steel prices - Report - KeyDocument 01 \r\n Westwood, T & Whittle, L 2018, Responsiveness of demand for structural pine to changes in timber and steel prices: A study using the FWPA softwood data series, Australian Bureau of Agricultural and Resource Economics and Sciences, Canberra, July. CC BY 4.0.<br/>Responsiveness of demand for structural pine to changes in timber and steel prices - Report - KeyDocument 02 \r\n Westwood, T & Whittle, L 2018, Responsiveness of demand for structural pine to changes in timber and steel prices: A study using the FWPA softwood data series, Australian Bureau of Agricultural and Resource Economics and Sciences, Canberra, July. CC BY 4.0.<br/>Authoritative descriptive metadata for: Responsiveness of demand for structural pine to changes in timber and steel prices: A study using the FWPA softwood data series - Metadata in ISO 19139 format\r\n<br/>
Australian dairy: financial performance of dairy farms, 2015-16 to 2017-18
No full textOverview \r\n This report presents the detailed financial performance estimates of dairy farmers for 2015-16, 2016-17 and 2017-18, and discusses incomes, investment, farm debt, and costs of production in a historical context. The report draws on data from the ABARES annual Australian Dairy Industry Survey (ADIS). \r\n\r\n The report will be published as a series of chapters online throughout the year. The web-reports are a new format for publishing this information - aimed at delivering information to stakeholders as the chapters are completed rather than as one annual report. \r\n\r\nAuthoritative descriptive metadata for: Australian dairy: financial performance of dairy farms, 2015-16 to 2017-18 - Metadata in ISO 19139 format\r\n<br/>
Climatic suitability of Australia's production forests for myrtle rust
No full textMyrtle rust disease has caused defoliation and death of trees of rainforest species in New South Wales and Queensland, and has also been responsible for significant damage to eucalypt plantations in South America. This report combines climatic suitability modelling for myrtle rust across Australia with spatial data on Australia's production forests and forecast wood availability. The results show that 9.1 per cent of Australia's forecast available volume of plantation eucalypt logs, and 22 per cent of Australia's forecast available volume of public native forest eucalypt logs, derive from areas predicted to be highly suitable climatically for myrtle rust. The report also discusses the differences between an area being highly suitable climatically for myrtle rust, and a potential impact on wood production.Climatic suitability of Australia's production forests for myrtle rust - Report - KeyDocument 01 \r\n Singh, S, Senarath, U, & Read, S 2016, Climatic suitability of Australia's production forests for myrtle rust. ABARES Research Report 16.7, Canberra, August. CC BY 3.0.<br/>Climatic suitability of Australia's production forests for myrtle rust - Report - KeyDocument 02 \r\n Singh, S, Senarath, U, & Read, S 2016, Climatic suitability of Australia's production forests for myrtle rust. ABARES Research Report 16.7, Canberra, August. CC BY 3.0.<br/>Authoritative descriptive metadata for: Climatic suitability of Australia's production forests for myrtle rust - Metadata in ISO 19139 format\r\n<br/>
Australia's cost recovery arrangements for export certification : implications for Australian agriculture
No full text\r\nThe Department of Agriculture and Water Resources is currently redesigning its cost recovery arrangements for export certification services. The Cost Recovery Taskforce requested that ABARES analyse the effect of full cost recovery of the cost of export certification services on the competitiveness of Australian agricultural exports. The report: \r\n• estimates how full cost recovery affects the value of Australia's agricultural and fisheries exports \r\n• considers the farm-gate impact of exporters passing costs on to producers under a range of scenarios \r\n• investigates cost recovery arrangements in competitor countries for major export commodities. \r\n Key Issues \r\n\r\n ABARES modelling and analysis indicates that full recovery of the department's export certification costs has a small impact on the value of agricultural exports - less than 1 per cent for each of the export commodities considered. • The largest reduction in value occurs in beef and sheep meat exports, which are estimated to decrease by 0.79 per cent and 0.54 per cent, respectively. Beef and sheep meat exports have the highest industry cost of export certification relative to the value of exports. \r\n ABARES modelling also indicates that export certification charges have a small impact on farm gate receipts. • Livestock producers' farm gate receipts are estimated to fall between 0.57 and 0.74 per cent. In dollar terms, the impacts range from about 2440 for a typical sheep-beef farm. \r\n• Cropping and dairy producers' farm gate receipts are estimated to fall by up to 0.23 per cent. In dollar terms, the impacts range from about 1884 for a typical wheat and other crops farm. \r\n• Horticulture farm receipts for macadamia, almond and orange producers are estimated to fall between 0.11 and 0.28 per cent, based on the average volume of product grown per farm. In dollar terms, the impacts range from 2415 for an almond farmer, based on the average volume of product grown per farm. \r\n• Horticulture farm receipts for table grape producers are estimated to fall by 0.38 per cent ($1636) based on the average volume of product grown per farm. \r\n ABARES investigated the cost recovery arrangements of Canada, Chile, Germany, Ireland, the Netherlands, New Zealand, Poland, Thailand and the United States. • All these countries have arrangements in place to recover some or all of the costs of providing export certification services. \r\n\r\n\r\n\r\n\r\nAustralia's cost recovery arrangements for export certification : implications for Australian agriculture report - KeyDocument 01 \r\n The report: estimates how full cost recovery affects the value of Australia's agricultural and fisheries exports; considers the farm-gate impact of exporters passing costs on to producers under a range of scenarios; investigates cost recovery arrangements in competitor countries for major export commodities. \r\n<br/>Australia's cost recovery arrangements for export certification : implications for Australian agriculture report - GeneralDownload 01 \r\n The report: estimates how full cost recovery affects the value of Australia's agricultural and fisheries exports; considers the farm-gate impact of exporters passing costs on to producers under a range of scenarios; investigates cost recovery arrangements in competitor countries for major export commodities. \r\n<br/>Authoritative descriptive metadata for: Australia's cost recovery arrangements for export certification : implications for Australian agriculture - Metadata in ISO 19139 format\r\n<br/>
Australian Crop Report: June 2017 No. 182
No full textThe report is a quarterly report with a consistent and regular assessment of crop prospects for major field crops, forecasts of area, yield and production and a summary of seasonal conditions on a state by state basis. \r\n\r\n In this edition of the Australian crop report, ABARES will release its first set of forecasts of winter crop production in 2017-18 and estimates of summer crop production in 2016-17. \r\n\r\n Key issues • The start of the 2017-18 winter crop season was mixed. Autumn rainfall was generally favourable in cropping regions in the eastern states (excluding South Australia), which resulted in favourable levels of soil moisture in these regions. In most cropping regions in Western Australia and some key cropping regions in South Australia, autumn rainfall was below average, which led to unfavourable planting conditions during autumn and early winter in these regions. \r\n• Below average winter rainfall is likely in most major cropping regions, according to the latest three-month rainfall outlook (June to August) issued by the Bureau of Meteorology on 25 May 2017. \r\n• The total area planted to winter crops is forecast to fall by around 1 per cent in 2017-18 to 22.5 million hectares. Area planted to cereal crops is expected to decrease but the area planted to canola, chickpeas and lentils is forecast to increase. Area planted to canola is forecast to rise in all major producing states, largely reflecting favourable expected returns compared with wheat, oats and barley. \r\n• Total winter crop production is forecast to decrease by 33 per cent in 2017-18 to 40.1 million tonnes, which largely reflects an assumed fall in average yields from the exceptionally high yields of 2016-17. \r\n• Total Australian summer crop production is estimated to have increased by 5 per cent in 2016-17 to 4 million tonnes because of large increases in cotton and rice production. \r\nAustralian crop report: June 2017 No. 182 - Report - KeyDocument 01<br/>Australian crop report: June 2017 No. 182 - Report - KeyDocument 02<br/>Crop data underpinning: Australian crop report: June 2017 No. 182 - Data 1<br/>State data underpinning: Australian crop report: June 2017 No. 182 - Data 2<br/>Authoritative descriptive metadata for: Australian Crop Report: June 2017 No. 182 - Metadata in ISO 19139 format\r\n<br/>
Australian crop report: September 2015 No.175
No full textThe report is a quarterly report with a consistent and regular assessment of crop prospects for major field crops, forecasts of area, yield and production and a summary of seasonal conditions on a state by state basis. \r\n\r\n\r\n 2015-16 winter crop production \r\n\r\n Favourable seasonal conditions in most cropping regions in Australia during winter have resulted in improved prospects for 2015-16 winter crop production. \r\n\r\n The outlook for spring rainfall is favourable for most cropping regions in Australia. In its latest three-month rainfall outlook (September to November 2015), issued on 27 August 2015, the Bureau of Meteorology forecast that wetter than average spring is likely in most cropping regions in New South Wales, Victoria, South Australia and Western Australia. Close to average spring rainfall is likely in most cropping regions in Queensland. \r\n\r\n Total winter crop production is forecast to rise by 8 per cent in 2015-16 to 41.4 million tonnes, largely as a result of forecast production increases in Western Australia and New South Wales. Winter crop production is also expected to rise in Queensland and Victoria but remain largely unchanged in South Australia, compared with 2014-15. \r\n\r\n Wheat production is forecast to increase by 7 per cent in 2015-16 to 25.3 million tonnes and barley production is forecast to rise by 8 per cent to 8.6 million tonnes. In contrast, canola production is forecast to fall by 9 per cent to around 3.1 million tonnes. \r\n\r\n 2014-15 summer crop production \r\n\r\n Area planted to summer crops is forecast to increase by 1 per cent in 2015-16 to around 1.1 million hectares. \r\n\r\n Total summer crop production is forecast to fall by 2 per cent in 2015-16 to 3.9 million tonnes, reflecting an assumed fall in average yields from 2014-15. \r\n\r\n Area planted to grain sorghum is forecast to be largely unchanged in 2015-16 at 651 000 hectares. Assuming a return to average yields, production is forecast to fall by 4 per cent to 2 million tonnes.Australian crop report: September 2015 No. 175- Report - GeneralDownloads 01<br/>Australian crop report: September 2015 No. 175- Report - KeyDocument 01<br/>Crop data underpinning: Australian crop report: September 2015 No. 175 - Data 1<br/>State data underpinning: Australian crop report: September 2015 No. 175 - Data 2<br/>Authoritative descriptive metadata for: Australian crop report: September 2015 No.175 - Metadata in ISO 19139 format\r\n<br/>
CCS - MV Bluefin 2017 V01 TSG
No full textA Seabird model SBE-45 thermo-salinograph was installed in the carbon team’s container and measured seawater from the ship’s auxiliary seawater pump for the duration of the voyage.\n\nSurvey settings:\n\nA flow of 1.6-1.8 litres per minute was maintained through the instrument. Readings were recorded once per minute.\n\nCalibration Information:\n\nThe instrument is new and was calibrated by the manufacturer in 2017. Salinity samples were collected for later analysis and a correction will be applied if needed
CCS - MV Bluefin 2017 V01 CTD
No full textProject Overview: A range of solutions will be required to reach globally agreed emissions reductions targets for carbon dioxide (CO2). Carbon capture and storage (CCS) is part of the suite of technologies that will contribute to lowering atmospheric emissions of CO2 from Australia's energy system. There are a wide variety of technologies at various stages of technical and commercial readiness, with more development underway for cost effective CO2 capture and storage. Our research will provide new knowledge to inform cost-efficient measurement, monitoring and verification (MMV) of the environment of CCS projects in coastal waters.\n\n--o--\n\nBrief Description:\nA series of CTD casts were completed using a SBE25plus CTD profile combined with Seabird ECO55 water sampler accommodating six Niskin bottles. Water samples were taken from each cast using pre-programmed depths appropriate to the total water column depth which varied from 14 -20 m. Niskin bottles were closed on the down cast due to limitations of the firing software. The water temperature ranged between 18 and 20 degrees. Oxygen and nutrient samples were taken from most of the successful Niskin bottles samples. \n\nThe first three CTD casts were found to have the wrong time stamp as the CTD had been initialised in local time. This was corrected to UTC and the metadata for the casts updated.\n\nRelevant component details: make, model, serial number, firmware version, settings:\n\nSensor | Serial Number\nSBE25plus | 0251152\nTemperature | 03-6206\nConductivity | 04-4632\nPressure | 10654713\nOxygen Sensor (SBE 63) | 1669\nWet labs (ECO-BB ) | BBFL2BAC-120
Satellite Remote Sensing - Satellite Contributed Ocean Colour - SeaWIFS Chlorophyll Concentration in the Southern Ocean: Weekly, Johnson et al 2013
No full textStatement: Original Rrs data were from SeaWiFS reprocessing R2013.0 NASA GSFC http://oceandata.sci.gsfc.nasa.gov/SeaWiFS/Mapped/8Day/9km/Rrs/
See Johnson et.al. 2013 for full details.
****NETCDF FILENAMING CONVENTION FOR AQUA FILES****
The filenaming scheme puts a lot of useful metadata into the filename with the aim of making it easy to parse by machine and eye.
Folder D-20120802.G-0720.P-aqua.C-20120802082919.T-d263047n000000.S-m.E-definitive.Z-ok.R-20120802185051/ --
Folder D-20120802.G-0715.P-aqua.C-20120802111359.T-d549724n000000.S-mn.E-definitive.Z-ok.R-20120802185343/ --
Folder D-20120802.G-0710.P-aqua.C-20120802111224.T-d549724n000000.S-mn.E-definitive.Z-ok.R-20120802185344/ --
Folder D-20120802.G-0545.P-aqua.C-20120802101905.T-d549724n000000.S-na.E-definitive.Z-ok.R-20120802185437/ --
Folder D-20120802.G-0540.P-aqua.C-20120802101900.T-d549724n000000.S-cmna.E-definitive.Z-ok.R-20120802185314/ --
Folder D-20120802.G-0535.P-aqua.C-20120802101855.T-d549724n000000.S-cmna.E-definitive.Z-ok.R-20120802185436/ --
Folder D-20120802.G-0405.P-aqua.C-20120802084036.T-d549724n000000.S-qna.E-definitive.Z-ok.R-20120802185313/ --
Folder D-20120802.G-0400.P-aqua.C-20120802084028.T-d549724n000000.S-cqna.E-definitive.Z-ok.R-20120802185314/
Split the names on ‘.’, and then you have NAME-VALUE pairs where
D = GMT Date
G = GMT Acquisition
P = Platform
C = Creation date/time (yyyymmddhhmmss)
T = number of modis packet types (d=day packets, n=night packets)
S = contributing reception stations (a=Alice Springs, c=Crib Pt, m=Murdoch, q=AIMS, n=NASA DAAC)
E = Ephemeris (predicted or definitive)
Z = L1B processing status (should always be ok for these data)
R = date/time of processing of L2 Chl granule (but I forget what R stands for)<b>Credit</b><br/>Commonwealth Scientific and Industrial Research Organisation (CSIRO)<b>Credit</b><br/>Institute for Marine and Antarctic Studies (IMAS)<b>Credit</b><br/>Australian Research Council Centre of Excellence for Climate System Science<b>Credit</b><br/>Antarctic Climate and Ecosystems Cooperative Research Centre (ACE CRC)<b>Credit</b><br/>Australian Antarctic Division (AAD)<b>Credit</b><br/>Integrated Marine Observing System (IMOS).<b>Credit</b><br/>National Aeronautics and Space Administration (NASA)The Aqua and Orbview satellites carry a MODIS and SeaWIFS sensors (respectively) that observes sunlight reflected from within the ocean surface layer at multiple wavelengths. These multi-spectral measurements are used to infer the concentration of chlorophyll-a (Chl-a), most typically due to phytoplankton, present in the water. <br/><br/>There are multiple retrieval algorithms for estimating Chl-a and aggregating the data over time. This data set is a reprocessed copy of 9km monthly and 8-day versions produced globally by NASA, adjusted for the Southern Ocean south of latitude 30S. The full methodology is described in Johnson, R., Strutton, P.G., Wright, S.W., McMinn, A., Meiners, K.M., 2013. Three improved satellite chlorophyll algorithms for the Southern Ocean. Journal of Geophysical Research: Oceans. doi: 10.1002/jgrc.20270. It is expected that the data set will be periodically updated with contemporary data as it becomes available.<br/><br/>There are four sub-streams within this data set. A monthly and an 8-day series for MODIS/Aqua and similarly for SeaWIFS. Note that SeaWIFS ceased operation in late 2010 so there will be no further SeaWIFS data. <br/><br/>The data represented by this record is weekly data for SeaWIFS