Table 1.
ItC: Item code, EC: Element code, IC: Indicator code. Download of FAO data from http://faostat.fao.org on 27.10.2010 and from Worldbank from http://data.worldbank.org on 13.09.2011.
Table 2.
Regression parameters with linear time dependence for total calories for formulation gA (Eq 3).
Significance levels for p-values are denoted by (***): < 0.001, (**): ∈ [0.001, 0.01), (*): ∈ [0.01, 0.05), (.): ∈ [0.05, 0.1).
Table 3.
Statistical properties of regression models on total calorie demand (CT) and animal-based calorie share (CLS).
Significance levels for p-values are denoted by (***): < 0.001, (**): ∈ [0.001, 0.01), (*): ∈ [0.01, 0.05), (.): ∈ [0.05, 0.1).
Fig 1.
Model estimation for total calorie demand CT a) with formulation gA (Eq (3), SRES scenarios A1 & A2) and b) with formulation gB (Eq (5), SRES scenarios B1 & B2). Comparison of reported and modelled total calories given as frequency in percent of the number of data pairs (colorscale below). Lines denote the linear regression (solid, values see Table 3) and 1:1 line (dashed). Note log scale of axes.
Fig 2.
Model estimation for total calorie demand CT with formulations gA (red colors) and gB (blue colors). Predictions for years 1961, 1980, 2000, 2050 and 2100 (lines) as well as reported data for 1961, 1980 and 2000 (dots) with a) linear axes scale and b) logarithmic axes scale.
Table 4.
Regression parameters with declining time dependence for total calories for formulation gB (Eq 4) (RSE: residual standard error).
Significance levels for p-values are denoted by (***): < 0.001, (**): ∈ [0.001, 0.01), (*): ∈ [0.01, 0.05), (.): ∈ [0.05, 0.1).
Table 5.
Regression parameters of the multiple linear regression for animal-based calorie share hA (Eq 7).
Significance levels for p-values are denoted by (***): < 0.001, (**): ∈ [0.001, 0.01), (*): ∈ [0.01, 0.05), (.): ∈ [0.05, 0.1).
Fig 3.
Same as Fig 1 for animal-based calorie share CLS with formulation hA (Eq (8), SRES scenarios A1 & A2) and hB (Eq (8), SRES scenarios B1 & B2).
Fig 4.
Same as Fig 2 for animal-based calorie share CLS with formulation hA (Eq (8), SRES scenarios A1 & A2) and hB (Eq (8), SRES scenarios B1 & B2).
Table 6.
Regression parameters for animal-based calorie share hB (Eq 8).
Significance levels for p-values are denoted by (***): < 0.001, (**): ∈ [0.001, 0.01), (*): ∈ [0.01, 0.05), (.): ∈ [0.05, 0.1).
Table 7.
Significant trends (values only shown for p < 0.05) for total calorie demand (kcal capita−1 d−1 a−1) between 1988 and 2007 for FAO data and between 1990 and 2010 for all scenarios estimated using the Mann-Kendall test.
Table 8.
Significant centennial trends (values only shown for p < 0.05) for animal-based demand shares (kcal kcal−1 capita−1 day−1 0.01 a−1) between 1988 and 2007 for FAO data and between 1990 and 2010 for all scenarios estimated using the Mann-Kendall test.
Fig 5.
Total food energy demand projections per region over time for 4 SRES scenarios (1018 Joule a−1).
Figures consist of historical data by FAO (1961–2007, “History”), respective projections (1990–2100, “Scenario”).
Fig 6.
Comparison of estimates of total (left) and animal-based (right) calorie demand between values from the literature [17, 19–21] (x-axis) and own calculations (y-axis). Values are given for 2030 and 2050 as regional means (black dots) which are derived as population weighted averages of countries in the same regions as given in the literature and global means (red dots). Compare Tables (9, 10 and 11) and discussion in section on “Comparison of calorie demand projections to other studies”.
Table 9.
Comparison of projections in kcal capita−1 d−1.
Transforming the projections of Alexandratos et al. [18] for animal products into calorie values has been done by Valin et al. [19]. We aggregated our national values in order to match the FAO regions below. In comparison with values from FAOSTAT [1], we presume that (Table 2, [19]) refers to total animal-based calories. The B2-Regional scenario of Valin et al. [19] takes population and income projections of the B2-scenario of Nakicenovic et al. [8] and assumes that food demand evolves according to strong regional specifications. DC = Developing Countries, IC = Industrial Countries (including Australia, Japan and New Zewland), TC = Transition Countries. The following subregions belong to DC: SSA = Sub-Sahara Africa (excluding South Africa), MEA = Middle East and North Africa (including Turkey and Afghanistan), LAM = Latin America, SAS = South Asia, EAS = East Asia.
Table 10.
Comparison of projections in kcal capita−1 d−1.
Values extracted from Kruse [21]. We aggregated our national values in order to be comparable. ME = Middle East (including Turkey), LAM = Latin America, Asia (including Afghanistan), FSU = Former Soviet Union, EUR = Europe, NAM = North America.
Table 11.
Comparison of projections in kcal capita−1 d−1.
We aggregated our national values in order to match the regional values. The AGO scenario (Agrimonde Global Orchestration) is based on the Global Orchestration scenario of the Millenium Assessment report. SSA = Sub-Sahara Africa (including South Africa), MEA = Middle East and North Africa (including Turkey and Afghanistan), LAM = Latin America, Asia (including Afghanistan), FSU = Former Soviet Union, OECD (including Turkey).
Fig 7.
Same as Fig 5 for animal-based food energy demand projections per region over time for 4 SRES scenarios (1018 Joule a−1).
Fig 8.
Percentages of child mortality (a) and children underweight (b) against food demand for 4 years (denoted by colors). Data are taken from Von Grebmer et al. [49] and FAOSTAT [1]. Lines indicate the thresholds for calorie demand of 2000 and 2500 kcal capita−1 d−1, child mortality percentages of 5 and 10% and children underweight percentages of 10 and 20%.