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. Author manuscript; available in PMC: 2019 Mar 14.
Published in final edited form as: Nat Sustain. 2018 Sep 14;1(9):477–485.

Fig. 2. Externality costs of alternative production systems against land cost for five externalities in four agricultural sectors.

Fig. 2

All costs are expressed per tonne of production (so land cost, for instance, is in ha-years/tonne– i.e. the inverse of yield). Different externalities are indicated by background shading (grey = GHG emissions, blue = water use, pink = N emissions, purple = P emissions, buff = soil loss), and different sectors (Asian paddy rice, European wheat, Latin American beef, European dairy) are shown by icons. Points on plots derived from multi-site experiments (a, b, c) and LCAs (e) show values for systems adjusted for site and study effects via GLMMs of land cost and externality cost (for 95% confidence intervals, see Supplementary Fig. 1), while arrows show management practices with statistically-significant effects (whose 95% confidence intervals do not overlap zero in the GLMMs; Methods). In d (wheat and N emissions), progressively darker circles depict increasing nitrate application rate (0, 48, 96, 144, 192, 240 and 288 kg N/ha-year). In f (beef and GHG emissions, estimated by RUMINANT), different colours show different system types. In g-j (dairy and four externalities), circles and squares show results for conventional and organic systems, respectively (detailed in Supplementary Table 4). Spearman's rank correlation coefficients (p-values) are a. rice-rice: -0.51 (0.002), rice-cereal: -0.36 (0.06), b. 0.19 (0.26), c. -0.34 (0.14), d. -0.21 (0.66), e. 0.95 (0.001), f. 0.83 (< 0.001), g. 0.90 (0.08), h. 0.70 (0.23), i. 1.00 (0.02) and j. 1.00 (0.02). Note that these correlation coefficients do not necessarily reflect non-linear relationships (e.g., d) accurately.