Author
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AUBAULT, HELENE - Griffiths University |
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WEBB, NICHOLAS - New Mexico State University |
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STRONG, CRAIG - Australian National University |
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MCTAINSH, GRANT - Griffiths University |
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LEYS, JOHN - Non ARS Employee |
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SCANLAN, JOE - Department Of Agriculture - Australia |
Submitted to: Aeolian Research
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 12/13/2014 Publication Date: 3/5/2015 Publication URL: http://handle.nal.usda.gov/10113/60528 Citation: Aubault, H., Webb, N.P., Strong, C.L., Mctainsh, G.H., Leys, J.F., Scanlan, J.C. 2015. Grazing impacts on the susceptibility of rangelands to wind erosion: the effects of stocking rate, stocking strategy and land condition. Aeolian Research. 17:89-99. Interpretive Summary: Livestock production is thought to increase the susceptibility of the rangelands to wind erosion by reducing vegetation cover and modifying surface soil stability. However, research is yet to quantify the impacts of grazing land management on the erodibility of the Australian rangelands, or determine how these impacts vary among land types and over time. We present a simulation analysis that links a pasture growth and animal production model (GRASP) to the Australian Land Erodibility Model (AUSLEM) to evaluate the impacts of stocking rate, stocking strategy and land condition on the erodibility of four land types in western Queensland, Australia. Declining land condition, over stocking, and using inflexible stocking strategies have potential to increase land erodibility and accelerate soil erosion. However, land erodibility responses to grazing are complex and influenced by land type sensitivities to different grazing strategies and local climate characteristics. Land types which are more resilient to livestock grazing tend to be least susceptible to accelerated wind erosion. Increases in land erodibility are found to occur most often during climatic transitions when vegetation cover is most sensitive to grazing pressure. However, grazing effects are limited during extreme wet and dry periods when the influence of climate on vegetation cover is strongest. Technical Abstract: An estimated 110 Mt of dust is eroded by wind from the Australian land surface each year, most of which originates from the arid and semi-arid rangelands. Livestock production is thought to increase the susceptibility of the rangelands to wind erosion by reducing vegetation cover and modifying surface soil stability. However, research is yet to quantify the impacts of grazing land management on the erodibility of the Australian rangelands, or determine how these impacts vary among land types and over time. We present a simulation analysis that links a pasture growth and animal production model (GRASP) to the Australian Land Erodibility Model (AUSLEM) to evaluate the impacts of stocking rate, stocking strategy and land condition on the erodibility of four land types in western Queensland, Australia. Our results show that declining land condition, over stocking, and using inflexible stocking strategies have potential to increase land erodibility and amplify accelerated soil erosion. However, land erodibility responses to grazing are complex and influenced by land type sensitivities to different grazing strategies and local climate characteristics. Our simulations show that land types which are more resilient to livestock grazing tend to be least susceptible to accelerated wind erosion. Increases in land erodibility are found to occur most often during climatic transitions when vegetation cover is most sensitive to grazing pressure. However, grazing effects are limited during extreme wet and dry periods when the influence of climate on vegetation cover is strongest. Our research provides the opportunity to estimate the effects of different land management practices across a range of land types, and provides a better understanding of the mechanisms of accelerated erosion resulting from pastoral activities. The approach could help further assessment of land erodibility at a broader scale notably if combined with wind erosion models. |