Carbon, water and energy fluxes in agricultural systems of Australia and New Zealand

Cleverly, James, Vote, Camilla, Isaac, Peter, Ewenz, Cacilia, Harahap, Mahrita, Beringer, Jason, Campbell, David I., Daly, Edoardo, Eamus, Derek, He, Liang, Hunt, John, Grace, Peter, Hutley, Lindsay B., Laubach, Johannes, McCaskill, Malcolm, Rowlings, David, Rutledge Jonker, Susanna, Schipper, Louis A., Schroder, Ivan, Teodosio, Bertrand, Yu, Qiang, Ward, Phil R., Walker, Jeffrey P., Webb, John A., and Grover, Samantha P.P. (2020) Carbon, water and energy fluxes in agricultural systems of Australia and New Zealand. Agricultural and Forest Meteorology, 287. 107934.

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A comprehensive understanding of the effects of agricultural management on climate–crop interactions has yet to emerge. Using a novel wavelet–statistics conjunction approach, we analysed the synchronisation amongst fluxes (net ecosystem exchange NEE, evapotranspiration and sensible heat flux) and seven environmental factors (e.g., air temperature, soil water content) on 19 farm sites across Australia and New Zealand. Irrigation and fertilisation practices improved positive coupling between net ecosystem productivity (NEP = −NEE) and evapotranspiration, as hypothesised. Highly intense management tended to protect against heat stress, especially for irrigated crops in dry climates. By contrast, stress avoidance in the vegetation of tropical and hot desert climates was identified by reverse coupling between NEP and sensible heat flux (i.e., increases in NEP were synchronised with decreases in sensible heat flux). Some environmental factors were found to be under management control, whereas others were fixed as constraints at a given location. Irrigated crops in dry climates (e.g., maize, almonds) showed high predictability of fluxes given only knowledge of fluctuations in climate (R2 > 0.78), and fluxes were nearly as predictable across strongly energy- or water-limited environments (0.60 < R2 < 0.89). However, wavelet regression of environmental conditions on fluxes showed much smaller predictability in response to precipitation pulses (0.15 < R2 < 0.55), where mowing or grazing affected crop phenology (0.28 < R2 < 0.59), and where water and energy limitations were balanced (0.7 < net radiation ∕ precipitation < 1.3; 0.27 < R2 < 0.36). By incorporating a temporal component to regression, wavelet–statistics conjunction provides an important step forward for understanding direct ecosystem responses to environmental change, for modelling that understanding, and for quantifying nonstationary, nonlinear processes such as precipitation pulses, which have previously defied quantitative analysis.

Item ID: 73458
Item Type: Article (Research - C1)
ISSN: 1873-2240
Keywords: Agriculture, Eddy covariance, Environmental variability, Irrigation, Precipitation pulses, Wavelet-statistics conjunction
Copyright Information: © 2020 Elsevier B.V. All rights reserved.
Funders: Australian Research Council (ARC)
Projects and Grants: ARC LP140100871
Date Deposited: 05 Jul 2022 01:58
FoR Codes: 30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3004 Crop and pasture production > 300402 Agro-ecosystem function and prediction @ 100%
SEO Codes: 26 PLANT PRODUCTION AND PLANT PRIMARY PRODUCTS > 2699 Other plant production and plant primary products > 269999 Other plant production and plant primary products not elsewhere classified @ 100%
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