Toward optimisation of water use efficiency in dryland pastures using carbon isotope discrimination as a tool to select plant species mixtures.

Pastoral agriculture is important for supplying global demand for animal products but pasture productivity is often water limited. Increased plant diversity has been shown to increase water use efficiency (ω) and productivity under water limitation but the optimal mix of species varies spatially, dependent on climate, soil type, and plant water requirements. Consequently, a cost-effective method to screen for high ω plant species and mixes in situ at farm scale is needed. Using carbon isotope discrimination (∆ ¹³ C) to examine ω is attractive because the method integrates over useful time scales, does not modify the measurement environment, and is cost-effective. Field scale ω was measured using eddy covariance (EC) at two sites with contrasting plant diversity (2 species, 7 species) and compared to the seasonal progression of ω calculated from foliage ∆ ¹³ C (ω _∆ ). Soil water evaporation (E _S ) was removed from EC measured total ecosystem evaporation using a modelling approach and canopy ω (ω _C ) was calculated as gross primary production (GPP) divided by canopy evaporation. Mixed species foliage samples were harvested pre-grazing, dried, sub-sampled, ground, and the ratio of ¹³ C to ¹² C was measured. A strong positive correlation was found between ω _∆ and ω _C at both study sites (r ²  > 0.83, p < 0.01). In addition to bulk biomass samples, individual species were also harvested seasonally. Relative increases in both ω _∆ and production for some species showed that manipulation of pasture species mixtures may lead to increased ω. Combined with production monitoring, ∆ ¹³ C could be developed as a tool to optimise species selection for site specific climate and soil conditions to maximise ω and farm production and profit.
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