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Australian land-use and sustainability data: 2013 to 2050

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About this Collection

Australian land-use and sustainability data: 2013 to 2050


Using the Land-Use Trade-Offs (LUTO) model, this data collection was produced via a comprehensive, detailed, integrated, and quantitative scenario analysis of land-use and sustainability for Australia’s intensive-use agricultural land to 2050, under intersecting global change and domestic policies, and considering key uncertainties. We assess... more


Agricultural Economics Agricultural Land Planning Conservation and Biodiversity Economic Geography Environment Policy Environment and Resource Economics Natural Resource Management Simulation and Modelling


http://doi.org/10.4225/08/5756169E381CC


2012


2015


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CSIROEnquiries@csiro.au
1300 363 400

ecosystem services sustainability land-use change global policy scenarios climate change emissions abatement economics model temporal spatial GIS future governance strategic decision-making


LUTO_publicationsList.docx


LUTO_indicators.xlsx


LUTO_coreScenariosDescription.xlsx


LUTO is an integrated environmental and economic model which estimates Australian land use futures under alternative global change and policy scenarios. LUTO has been fully described, tested, applied, and evaluated (see Related Information). The LUTO model takes an agricultural land use map as the baseline, and then combines a range of environmental and economic data to identify potential land use change (agriculture, carbon plantings, environmental plantings, bioenergy, and biofuels) and corresponding supply of ecosystem services (agriculture, emissions abatement, water resources, biodiversity services, bioenergy, and biofuel production). The model works at a grid cell resolution of 0.01 degrees (~1.1 km) and an annual time-step from 2013 – 2050. The LUTO model is a bottom-up model which identifies the location, type, and timing of potential land use change given changes in the relative profitability of land use options as determined by productivity, prices, costs, and adoption behaviour. Key uncertainties were considered including different rates of land use change adoption and productivity growth. Future trajectories in external drivers and domestic policy which influence productivity, prices, and costs were also considered. These included a carbon price, energy price, and food demand as derived by integrated assessment of global outlooks, and the establishment of new markets for biofuel and biodiversity. The biofuel market assumes the availability of nearby demand for wheat crop grain and residue. The biodiversity market includes a discriminatory payment scheme where landholders are paid the opportunity cost of adoption environmental plantings. The payment budget included a 125 $M yr-1 base level plus a levy on carbon plantings. A range of models were used to estimate the future provision of ecosystem services from each land use. Agricultural yields were derived from census data by SLA, and apportioned to cells in the land use map. To compliment this we used the Agricultural Production Systems Simulator (APSIM) to quantify crop yields under climate change and crop residue availability for biofuel production. The 3PG2 forest growth model was used to estimate carbon sequestration from reforestation in the form of carbon plantings (fast-growing Eucalyptus monocultures) and environmental plantings (mixed local native species), and growth was modified according to climate change effects. A landscape hydrology model—AWRA-L—was used to estimate the change in water resource availability resulting from the increased interception and evapotranspiration of water induced by reforestation compared to crops/pasture. We used a generalised dissimilarity model (GDM) to identify biodiversity priorities for ecological restoration via environmental plantings. Priority areas were those that both increase the area and connectivity of remnant habitat and create new habitat in areas which become important for species conservation given future shifts in climate. High-performance computing techniques were used to run LUTO, with each of the 648 scenario combinations taking about 40 hours to run. LUTO identified potential land use transitions over space and time, and estimated the resulting impact on supply of the five ecosystem services. This updated version corrects an error that resulted in the under reporting of annualised economic returns to carbon and environmental plantings in the spreadsheets and video


This project was funded by CSIRO Agriculture, CSIRO Land and Water, and the Australian National Outlook initiative. Brett A. Bryan, Martin Nolan, Lisa McKellar, Jeffery D. Connor, David Newth, Tom Harwood, Darran King, Javier Navarro, Yiyong Cai, Lei Gao, Mike Grundy, Paul Graham, Andreas Ernst, Simon Dunstall, Florian Stock, Thomas Brinsmead, Ian Harman, Nicky J. Grigg, Michael Battaglia, Brian Keating, Alex Wonhas, Steve Hatfield-Dodds (2015). Land-use and sustainability under intersecting global change and domestic policy scenarios: trajectories for Australia to 2050. Global Environmental Change (in Review)


CSIRO Data Licence


CSIRO (Australia)


Bryan, Brett; Nolan, Martin; Brennan, Lisa; Connor, Jeff; Newth, David; Harwood, Tom; King, Darran; Navarro Garcia, Javier; Cai, Yiyong; Gao, Lei; Grundy, Mike; Graham, Paul; Ernst, Andreas; Dunstall, Simon; Stock, Florian; Brinsmead, Thomas; Harman, Ian; Grigg, Nicky; Battaglia, Michael; Keating, Brian; Wonhas, Alex; Hatfield-Dodds, Steve (2015): Australian land-use and sustainability data: 2013 to 2050. v3. CSIRO. Data Collection. http://doi.org/10.4225/08/5756169E381CC


All Rights (including copyright) CSIRO 2015.


The metadata and files are available to the public.

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Location Details

9°59′42″ S


44°0′18″ S


154°0′18″ E


112°30′18″ E


GDA94


About this Project

SIP 59 LUTO land use modelling science p


CSIRO Australian National Outlook: Modelling of Australian land-use and sustainability 2013 to 2050.


Brett Bryan


Modelling


Modelling of Australian land-use and sustainability 2013 to 2050.


Modelling


Brett Bryan


Martin Nolan


Lisa Brennan


Jeff Connor


David Newth


Tom Harwood


Darran King


Javier Navarro Garcia


Yiyong Cai


Lei Gao


Mike Grundy


Paul Graham


Andreas Ernst


Simon Dunstall


Florian Stock


Thomas Brinsmead


Ian Harman


Nicky Grigg


Michael Battaglia


Brian Keating


Alex Wonhas


Steve Hatfield-Dodds