Quantifying and mapping the human appropriation of net primary production in earth's terrestrial ecosystems

Haberl et al. 10.1073/pnas.0704243104.

Supporting Information

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SI Figure 2

Fig. 2. Map of the NPP of the potential natural vegetation (NPP₀).

SI Figure 3

Fig. 3. Map of the NPP of currently prevailing vegetation (NPP_act).

SI Figure 4

Fig. 4. Map of the amount of NPP remaining in ecosystems after harvest (NPP_t).

SI Figure 5

Fig. 5. Map of global HANPP in the year 2000 expressed as carbon flow.

Table 5. Range of wood harvest estimates

As the Food and Agriculture Organization (FAO) reports official statistical data whenever available, even if they appear to be implausible (1), we compare these FAO woodfuel estimates with other international and regional estimates (2-11). For each country with alternative statistics, we collected minimum and maximum estimates. Industrial wood harvest is taken from FAO statistics. SI Table 5 displays the range of wood harvest (total removals including bark) and the FAO-derived estimates aggregated to eight world regions. For the calculation of HANPP, we use the conservative estimate of FAO (12). Regional aggregation after Wirsenius (13).

1. Whiteman A, Broadhead J, Bahdon J (2002) Unasylva 53:41-45.

2. United Nations (2002) Energy Statistics Yearbook 1999 (United Nations, New York).

3. Food and Agriculture Organization (1999) Production, Utilization and Marketing of Woodfuel in Lao PDR National Workshop Vientianne November 1997 (Food and Agriculture Organization, Rome).

4. Food and Agriculture Organization (1997) Review of Wood Energy Data in RWEDP Member Countries, Field Document no 47 (Regional Wood Energy Development Programme in Asia, Bangkok, ).

5. Food and Agriculture Organization (1997) Regional Study on Wood Energy Today and Tomorrow in Southeast Asia. Field Document No. 50. (Regional Wood Energy Development Programme in Asia, Bangkok, Thailand).

6. Food and Agriculture Organization (1998) Global Fibre Supply Model (Food and Agriculture Organization, Rome).

7. Jensen M (1995) Woodfuel Productivity of Agroforestry Systems in Asia, a Review of Current Knowledge (Food and Agriculture Organization Regional Wood Energy Development Programme, Bangkok, Thailand).

8. Amous S (1999) The Role of Wood Energy in Africa (Food and Agriculture Organization, Rome).

9. Lefevre T, Todoc J, Timilsina GR (1997) The Role of Wood Energy in Asia (Food and Agriculture Organization, Rome).

10. Akyol H, Rivero S (1998) The Role of Wood energy in the Near East (Food and Agriculture Organization, Rome).

11. European Commission-Food and Agriculture Organization Partnership Programme (2002) An Overview of Forest Products Statistics in South and Southeast Asia (Food and Agriculture Organization Regional Office for Asia and the Pacific, Bangkok, Thailand).

12. Food and Agriculture Organization (2004) FAOSTAT 2004, FAO Statistical Databases: Agriculture, Fisheries, Forestry, Nutrition (Food and Agriculture Organization, Rome).

13. Wirsenius S (2000) Human Use of Land and Organic Materials, Modeling the Turnover of Biomass in the Global Food System (Chalmers Univ, Göteborg, Sweden).

Table 6. Definition of regions used in our calculation

HANPP calculations are performed for 161 countries (not differentiating Belgium-Luxembourg). The regional grouping is based on the classification of the macro geographical (continental) regions and geographical subregions as defined by the United Nations Statistical Division (1). *, not differentiated.

1. United Nations Statistical Division (2006) Composition of Macro Geographical (Continental) Regions, Geographical Sub-regions, and Selected Economic and other Groupings, http://unstats.un.org/unsd/methods/m49/m49regin.htm (United Nations Statistical Division, New York).

Table 7. Harvest factors, recovery rates, loss factors, and above/belowground ratios used to extrapolate NPP_h and NPP_act from agricultural statistics

NPP_act on cropland is defined as the sum of harvested NPP as reported in statistics and other fractions not accounted for in agricultural statistics, i.e. aboveground crop residues (e.g. straw, stover), NPP losses during the growth period, losses due to herbivory, and the NPP of weeds and belowground NPP. The mass of crop residues is calculated with crop-specific and region-specific information on harvest indices taken from the literature (1-3). The derived harvest factors distinguish between 17 groups of crops and eight world regions (a). Recovery rates (b) are used to distinguish between harvested/recovered and unused residues on the basis of region and crop-specific recovery rates (2). Loss factors, derived from ref. 4, are used to account for NPP losses during the growth period, losses due to herbivory, and the NPP of weeds. Belowground NPP, i.e. NPP allocated to roots, tubers etc., is calculated by using the ratio of belowground to aboveground NPP taken from ref. 5.

1. Evans LT (1993) Crop Evolution, Adaption and Yield (Cambridge Univ Press, Cambridge).

2. Wirsenius S (2000) Human Use of Land and Organic Materials, Modeling the Turnover of Biomass in the Global Food System (Chalmers University, Göteborg, Sweden).

3. Wirsenius S (2003) Agric Syst 77:219-255.

4. Oerke E-C, Dehne H-W, Schönbeck F, Weber A (1994) Crop Production and Crop Protection, Estimated losses in major food and cash crops (Elsevier Science BV, Amsterdam).

5. Saugier B, Roy J, Mooney HA (2001) in Terrestrial Global Productivity, eds. Roy J, Saugier B, Mooney HA (Academic, San Diego), pp 543-557 .

Table 8. Wood recovery rates and wood densities for regions

In countries included in the TBFRA2000 statistical database (1), we calculated recovery rates in forestry by comparing fellings and removals. Fellings are defined as the average annual standing volume of all trees, living or dead, measured overbark felled during the given reference period, including the volume of trees or parts of trees not removed from the forested land, silvicultural and precommercial thinnings, cleanings left in the forest, and natural losses that are recovered. Removals only include fellings that are actually removed from the forest. The recovery rate was calculated as the ratio of removals to fellings. For tropical countries, literature data on recovery rates (2) are used to account for harvest losses. For woodfuel harvest in tropical countries, we increased these recovery rates by 50% in order to reflect higher collection rates in fuelwood gathering (values in parentheses). A comparison of this approach with assessments based on biomass expansion factors (3, 4) shows that expansion factors results in an estimate of wood fellings, which is 50-70% higher than the approach based on recovery rates used here. For TBFRA countries, we calculated average bark factors defined as wood underbark as a percentage of wood overbark. For all non-TBFRA countries, we assume a bark factor of 90%. Wood densities used were adopted from refs. 3-5. The regional aggregation is based on ref. 1.

1. United Nations (2000) Forest Resources of Europe CIS, North America, Australia, Japan and New Zealand (industrialized temperate/boreal countries), UN-ECE/FAO Contribution to the Global Forest Resources Assessment 2000, Main Report ECE/TIM/SP/17 (United Nations Publications, New York, Geneva).

2. Pulkki RE (1997) Literature Synthesis on Logging Impacts in Moist Tropical Forests, Global Fibre Supply Study Working Paper GFSS/WP/06 (Food and Agriculture Organization, Rome).

3. Penman J, Gytarsky M, Hiraishi T, Krug T, Kruger D, Pipatti R, Buendia L, Miwa K, Ngara T, Tanabe K, Wagner F (2003) Good Practice Guidance for Land Use, Land-Use Change and Forestry (Institute for Global Environmental Strategies-Intergovernmental Panel on Climate Change, Kanagawa, Japan).

4. Brown S (1997) Estimating Biomass and Biomass Change of Tropical Forests, a Primer (Food and Agriculture Organization, Rome).

5. Brown S, Lugo AE (1984) Science 223:1290-1293.

Table 9. Input data used for calculating country-level feed balances of livestock