Remotely sensed agricultural grassland productivity responses to land use and hydro-climatic drivers under extreme drought and rainfall
Article
Article Title | Remotely sensed agricultural grassland productivity responses to land use and hydro-climatic drivers under extreme drought and rainfall |
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ERA Journal ID | 1951 |
Article Category | Article |
Authors | Kath, Jarrod (Author), Le Brocque, Andrew (Author), Reardon-Smith, Kathryn (Author) and Apan, Armando (Author) |
Journal Title | Agricultural and Forest Meteorology |
Journal Citation | 268, pp. 11-22 |
Number of Pages | 12 |
Year | 2019 |
Publisher | Elsevier |
Place of Publication | Netherlands |
ISSN | 0168-1923 |
1873-2240 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.agrformet.2019.01.007 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S0168192319300073 |
Abstract | Climate change is expected to increase the frequency and intensity of drought globally with potentially significant consequences for grasslands. We examined grassland responses to a long-term drought on the Darling Downs, eastern Australia, using the Enhanced Vegetation Index (EVI), a remotely sensed measure of primary productivity. This extreme drought period had rainfall deficits comparable to the hottest and driest projected climate change scenarios for 2030 and was followed by extreme rainfall. This juxtaposition allowed investigation of grassland dynamics (decline and recovery) under extreme climatic variability. Our aim was to determine whether factors associated with grassland decline during extreme drought are the same as those that drive recovery post drought. There is limited knowledge about whether the determinants of grassland decline and recovery are consistent, but this information is important for understanding how best to reduce grassland decline, without inhibiting recovery. We calculated EVI (Enhanced Vegetation Index) trends at 2549 grassland sites situated in an agricultural landscape and used boosted regression trees to model these against multiple hydroclimatic and land use factors. As anticipated, hydro-climatic variables were key drivers of EVI trends in both the drought and wet phases, with higher soil moisture corresponding to less decline in the drought phase and enhanced recovery in the wet phase; however, land use and plant trait variables were also important predictors of EVI trends. Higher proportions of dryland agriculture in the local landscape, high C3:C4 ratios and lower proportions of woody vegetation in the local landscape were associated with negative EVI trends (i.e. greater decline) during drought, but had inverse or negligible effects during the post drought recovery phase. Our results suggest that mitigating decline and fostering grassland recovery following drought requires considering multiple hydro-climatic, land use and plant trait drivers and how their importance changes under drought and wet |
Keywords | extreme weather; millennium drought; resilience; pasture; remote sensing |
ANZSRC Field of Research 2020 | 410102. Ecological impacts of climate change and ecological adaptation |
300402. Agro-ecosystem function and prediction | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | International Centre for Applied Climate Science |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q4zyz/remotely-sensed-agricultural-grassland-productivity-responses-to-land-use-and-hydro-climatic-drivers-under-extreme-drought-and-rainfall
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