Schiller et al. (2025) Optimising Long-Range Agricultural Land Use Under Climate Uncertainty

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Identification

• Journal: Agriculture
• Year: 2025
• Date: 2025-10-14
• Authors: Karin Schiller, James Montgomery, Marcus Randall, Andrew Lewis, Muhammad Shahinur Alam
• DOI: 10.3390/agriculture15202133

Research Groups

Not explicitly mentioned in the provided text.

Short Summary

This paper introduces the spatio-temporal agricultural land use sequencer (STALS) model to determine climate-aware annual crop land uses for the Murrumbidgee Irrigation Area, finding that higher-value crops like horticulture can maximize regional economic benefit with minimal water usage under climate change.

Objective

• To develop and apply a spatio-temporal agricultural land use sequencer (STALS) model to determine feasible climate-aware annual crop land uses that maintain profitable and resilient agriculture in the Murrumbidgee Irrigation Area under a changed climate.

Study Configuration

• Spatial Scale: Regional (Murrumbidgee Irrigation Area, Australia)
• Temporal Scale: Long-term planning with annual resolution for crop land uses.

Methodology and Data

• Models used: Spatio-temporal agricultural land use sequencer (STALS) model, mathematical modelling and optimisation.
• Data sources: Not explicitly mentioned in the provided text, but implied to include climate and agricultural production data.

Main Results

• The analysis identified two distinct land-use possibilities: one with a concentrated crop mix and another more diverse.
• Both scenarios suggest that higher-value crops, such as horticultural species, will maximize regional economic benefit.
• This economic maximization is achieved with comparable minimal water usage under climate change conditions.
• A transformation of current land use is necessary to maintain regional agricultural economic benefit under projected reduced water availability and increased temperature.

Contributions

• Development and application of the novel spatio-temporal agricultural land use sequencer (STALS) model for climate-aware land-use planning.
• Providing specific, data-driven insights into optimal land-use transitions (e.g., towards higher-value horticulture) to maintain regional economic benefit and water efficiency under future climate conditions.

Funding

Not explicitly mentioned in the provided text.

Citation

@article{Schiller2025Optimising,
  author = {Schiller, Karin and Montgomery, James and Randall, Marcus and Lewis, Andrew and Alam, Muhammad Shahinur},
  title = {Optimising Long-Range Agricultural Land Use Under Climate Uncertainty},
  journal = {Agriculture},
  year = {2025},
  doi = {10.3390/agriculture15202133},
  url = {https://doi.org/10.3390/agriculture15202133}
}