Data

LMA Risk maps at Shire scale

The University of Queensland
Associate Professor Andries Potgieter (Aggregated by) Associate Professor Andries Potgieter (Aggregated by) Dr Jason Brider (Aggregated by) Dr Robert Armstrong (Aggregated by) Dr Robert Armstrong (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.48610/1774e6f&rft.title=LMA Risk maps at Shire scale&rft.identifier=RDM ID: cd3d1db0-326e-11ee-a444-4385de02d41d&rft.publisher=The University of Queensland&rft.description=A data collection of geospatial and temporal maps, and a spreadsheet, of LMA risks at Shire level for a specified set of initial flowering dates. The shire scale LMA risk analysis applied the LMA incidence model within a modified version of Oz-Wheat (Potgieter et al. 2006) to over 1800 contributing climate stations across the wheat-belt. For this purpose, Oz-Wheat utilises daily maximum and minimum temperatures from the SILO (Scientific Information for Landowners) patch point database. A phenological modelling approach based on APSIM (Keating et al. 2003) is applied to track the flowering to physiological maturity period. Multiple flowering dates were prescribed to represent a range of earlier and later flowering times across the wheat-belt, including 1 Aug, 15 Aug, 1 Sep, 15 Sep, 1 Oct, 15 Oct, and 1 Nov. LMA incidence modelling was applied at station level from 1991 – 2020 to quantify the year-to-year variability of LMA incidence (magnitude). The magnitude was then scaled to a binary value of 0 (no LMA) and 1 (LMA occurred). LMA risk at each station was quantified as the frequency (%) of years with LMA incidence over the 30 years of simulation results. A station weighted average for LMA risk was obtained at each shire. LMA risks mapped at Shire level were defined across a range of classes including 0 (or nil), < 10%, 10-20%, 20-30%, 30-40%, 40-50% and > 50% (or at least 1 in 2 years).&rft.creator=Associate Professor Andries Potgieter&rft.creator=Associate Professor Andries Potgieter&rft.creator=Dr Jason Brider&rft.creator=Dr Robert Armstrong&rft.creator=Dr Robert Armstrong&rft.creator=Professor Graeme Hammer&rft.creator=Professor Graeme Hammer&rft.date=2023&rft_rights= http://guides.library.uq.edu.au/deposit_your_data/terms_and_conditions&rft_subject=eng&rft_subject=flowering date&rft_subject=physiological maturity period&rft_subject=geospatial and temporal maps&rft_subject=Oz-Wheat&rft_subject=Agricultural spatial analysis and modelling&rft_subject=Agriculture, land and farm management&rft_subject=AGRICULTURAL, VETERINARY AND FOOD SCIENCES&rft_subject=Geospatial information systems and geospatial data modelling&rft_subject=Geomatic engineering&rft_subject=ENGINEERING&rft.type=dataset&rft.language=English Access the data
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r.armstrong1@uq.edu.au
Queensland Alliance for Agriculture and Food Innovation

Full description

A data collection of geospatial and temporal maps, and a spreadsheet, of LMA risks at Shire level for a specified set of initial flowering dates. The shire scale LMA risk analysis applied the LMA incidence model within a modified version of Oz-Wheat (Potgieter et al. 2006) to over 1800 contributing climate stations across the wheat-belt. For this purpose, Oz-Wheat utilises daily maximum and minimum temperatures from the SILO (Scientific Information for Landowners) patch point database. A phenological modelling approach based on APSIM (Keating et al. 2003) is applied to track the flowering to physiological maturity period. Multiple flowering dates were prescribed to represent a range of earlier and later flowering times across the wheat-belt, including 1 Aug, 15 Aug, 1 Sep, 15 Sep, 1 Oct, 15 Oct, and 1 Nov. LMA incidence modelling was applied at station level from 1991 – 2020 to quantify the year-to-year variability of LMA incidence (magnitude). The magnitude was then scaled to a binary value of 0 (no LMA) and 1 (LMA occurred). LMA risk at each station was quantified as the frequency (%) of years with LMA incidence over the 30 years of simulation results. A station weighted average for LMA risk was obtained at each shire. LMA risks mapped at Shire level were defined across a range of classes including 0 (or nil), < 10%, 10-20%, 20-30%, 30-40%, 40-50% and > 50% (or at least 1 in 2 years).

Issued: 2023

Data time period: 2020 to 2023

Data time period: Data collected from: 2020-01-01T00:00:00Z
Data collected to: 2023-01-01T00:00:00Z

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Subjects
Agricultural, Veterinary and Food Sciences | Agricultural Spatial Analysis and Modelling | Agriculture, Land and Farm Management | Engineering | Geomatic Engineering | Geospatial Information Systems and Geospatial Data Modelling | Oz-Wheat | eng | flowering date | geospatial and temporal maps | physiological maturity period |

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local : UQ:289097

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local : UQ:06510ce

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