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Ecological Embeddedness of the Economy

This paper analyses the development of humanity's economic activities from 1700 to 2000 based on a socioecological perspective. The global growth of human population and production in terms of monetary flows (GDP) are complemented with data that demonstrate the ecological "embeddedness" of human economic activities. The article assembles data drawn from the literature and from unpublished work to draw a first, still sketchy, picture of major trends during the last 300 years. The analysis is based on three global regions, the industrial core, east Europe and the former Soviet Union and the developing countries. The analysis is based on the socio-economic metabolism concept, in particular material and energy flow accounting. The findings suggest that resource constraints as well as limits to the capacity of the biosphere to safely absorb emissions and waste will not permit a global transition towards the industrial society according to the pattern currently observable in the industrial core.

Ecological Embeddedness of the Economy

A Socioecological Perspective on Humanity’s Economic Activities 1700-2000

This paper analyses the development of humanity’s economic activities from 1700 to 2000 based on a socioecological perspective. The global growth of human population and production in terms of monetary flows (GDP) are complemented with data that demonstrate the ecological “embeddedness” of human economic activities. The article assembles data drawn from the literature and from unpublished work to draw a first, still sketchy, picture of major trends during the last 300 years. The analysis is based on three global regions, the industrial core, east Europe and the former Soviet Union and the developing countries. The analysis is based on the socio-economic metabolism concept, in particular material and energy flow accounting. The findings suggest that resource constraints as well as limits to the capacity of the biosphere to safely absorb emissions and waste will not permit a global transition towards the industrial society according to the pattern currently observable in the industrial core.


ocusing on the analysis of stocks and flows of money, (neo)classical economists have derived an impressive body of theory, models, and methods for the analysis of economic systems. This purely monetary, “chrematistic” approach has, however, so far not been successful in adequately tackling the challenge of sustainability [Martinez-Alier 1987]. The socioeconomic metabolism approach [e g, Ayres and Simonis 1994; Matthews et al 2000; Fischer-Kowalski 1998; Fischer-Kowalski and Hüttler 1998; Weisz et al 2006] has been developed in the past decades as a means to account for society’s use of materials and energy [Haberl 2001] in a way that allows a description of economic processes in biophysical terms. In this article we use the so-called “materials and energy flow analysis” (MEFA) framework [Haberl et al 2004], an integrated toolkit to derive a representation of biophysical aspects of economic systems that is compatible with standard monetary economic statistics (e g, Sytem of National Accounts-SNA), to analyse the ecological “embeddedness” [Martinez-Alier 1999] of socio-economic activities.

Drawing from empirical research of the author and his colleagues in the last 15 years, the paper presents a global perspective on the transition from the agrarian to the industrial mode of subsistence. Changes in material and energy flows and their impacts on marine and terrestrial ecosystems – measured as human appropriation of net primary production or HANPP – in the last 200-300 years are discussed and contrasted with the standard “monetary” representation in terms of GDP statistics.

Global Economic Development 1700-2000: A Chrematistic Perspective

In this section we briefly discuss the development of the world economy as portrayed by the most widely used, conventional (that is, monetary) economic indicator: gross domestic product (GDP). The GDP measures the monetary value of all goods and services produced in an economy in one year. Despite its well known shortcomings, it is widely used as a measure of economic activities due to its advantages, including the following: (a) GDP accounts are meanwhile fairly standardised across countries and are widely used in policy discussions, modelling and scientific analyses, (b) they can be cross-checked in three ways [Maddison 2005]: From the income side, GDP is the sum of wages, rents and profits, from the demand-side it is the sum of final expenditures by consumers, investors and government, and from the production side it equals the value added of all sectors of the economy net of double-counting (inter-industry deliveries).

This section is based on the work of a prominent historical economist, Angus Maddison (2001), who used purchasing power parities to convert all GDP estimates to 1990 international Geary Khamis dollars, probably one of the most reliable and informative conversion methods in this context [Maddison 2005]. We use a simple, but nevertheless informative breakdown of the world economy in three groups of countries:

  • The “industrial core” includes western Europe, the US, Canada, Australia and New Zealand (a group of countries denoted as “Western Offshoots” by Maddison 2001) and Japan.
  • The second group includes east Europe and the former Soviet Union (abbreviated E Europe and FSU); that is, the formerly centrally-planned economies.
  • All other countries are lumped together in a group denoted as “developing countries,” although we are aware that this group also includes fairly industrialised countries such as Israel and South Africa or the oil producing countries of west Asia as well as the least-developed countries (the latter represent about 14 per cent of the population of that aggregate).
  • Figure 1 shows that world population grew by a factor of about

    9.8 in the last 300 years. Developing countries (which grew by

    Figure 1: Global Population, Total GDP and Per Capita GDP 1700-2000

    (a) World Population

    (b) Global GDPDeveloping coun trie s E Eu ro pe a n d F S U Ind ustrial co re 6,000 5,000 4,000 3,000 2,000 1,000 0 Population (million) 1700 1750 1800 1850 1900 1950 2000
    (c) Per Capita GDP Developing countries E Europe and FSU Industrial core 1700 1750 1800 1850 1900 1950 2000 35,000 30,000 25,000 20,000 15,000 10,000 5,000 0 GDP (billion 1990 int $/yr)
    Industrial core E Europe and FSU Developing countries Global average 1700 1750 1800 1850 1900 1950 2000 25,000 20,000 15,000 10,000 5,000 0 Per capita GDP (1990 int $/cap/yr)

    Note: Monetary values are 1990 international Geary-Khamis $, i e, PPP

    corrected values. Source: Maddison 2001.

    a factor of 10.4) and east Europe/FSU (9.1) grew a bit faster than the industrial core (7.6), but the differences in population growth between these three large world regions are small compared to the differences in GDP growth. Total GDP grew by a factor of 181 in the industrial core, a factor of 67 in east Europe/ FSU and only 57 in the developing countries. Total global GDP rose by a factor of 91. Disparities in GDP growth are even larger when GDP is expressed on a per capita basis: Per capita GDP grew by a factor of 24.4 in the industrial core, which was much faster than the global average of 9.3, whereas growth lagged behind in developing countries (5.5) and east Europe/FSU (7.4). Note that the decline in per capita GDP in east Europe/FSU most probably reflects two separate processes which are difficult to disentangle [Maddison 2005]: (a) A real reduction in GDP following the breakdown of communism and (b) changes in the accounting system that are hard to correct. Although attempts at correcting the accounts have been made, comparability of data for this region for the time period of 1920-50 to 1990 with GDP data derived from standard SNA methods in other countries is still probably less than perfect.

    Taken together, the data presented in Figure 1 corroborate the well known picture that about one quarter to one-third of the world population has managed to escape poverty by embarking on a process often called “industrialisation” (a multifaceted notion with different meanings), while about two thirds to three quarters of the world population are in the midst of a transition process from agrarian subsistence to industrial society – of course at various stages.

    The World 2000: A Socioecological Perspective

    This section analyses the three large country aggregates introduced in the last section in a multidimensional fashion. In order to demonstrate the ecological “embeddedness” [Martinez-Alier 1999] of economic activities we discuss biophysical dimensions of economic activities, above all the use of materials, energy, and land. Table 1 gives an overview of the three regions. The industrial core covers about 24 per cent of the planet’s terrestrial surface (excluding Antarctica) but is only inhabited by about 14 per cent of the world population. Despite its limited extent and population, about 53 per cent of the global GDP is generated there. By contrast, the developing countries cover 59 per cent of the Earth’s surface, are inhabited by 79 per cent of the world population, but have only 41 per cent of global GDP at their disposal.


    In order to describe resource extraction we here report figures on “Domestic Extraction” as calculated in material flow accounts [see Eurostat 2001 and Weisz et al 2006 for methodological details]. According to these figures, the industrial core contributes 37 per cent to the global total, east Europe and FSU 10 per cent and the developing countries 53 per cent (Table 1). The picture is similar when we look at energy use, which we here analyse based on the concept of “energetic metabolism” [Haberl 2001]. In contrast to conventional energy balances that only report on technical energy flows, we here include all biomass “metabolised” by society. The vast majority of this biomass is used as feed for livestock or food for humans. We here report the indicator “Domestic Energy Consumption”. With respect to energy use, the industrial core’s share of the global total is 43 per cent, that of east Europe and the FSU 11 per cent, while the developing countries have only 46 per cent at their disposal.

    In order to describe the intensity of land use on the territory of our three country aggregates we use the “human appropriation of net primary production” or HANPP [Vitousek et al 1986]. HANPP is an aggregate measure of the impact of land use on the availability of trophic energy in ecosystems. It reveals

    Figure 2: Global Resource Extraction in the Year 2000

    (a) Total Extraction

    (b) Extraction Per Capita and Year



    60 50

    Fossil fuels Fossil fuels

    Domestic extraction (billion tonnes/year)

    DE per capita (tonnes/capita/year)



    Construction 15 Construction

  • Ores
  • Biomass
  • Biomass

    510 0


    Industrial core

    E Europe and FSU

    Developing countries


    Industrial core

    E Europe and FSU

    Developing countries


    leUg Fossil fuels Construction Ores Biomass 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0DE per unit of GDP (tonnes/1000$) (c) Extraction Per Unit of GDP (d) Extraction Per Unit Area and Year Fossil fuels Construction Ores Biomass 700 600 500 400 300 200 100 0DE per unit area (tonnes/km2 /year)

    Industrial core

    E Europe and FSU

    Developing countries


    Industrial core

    E Europe and FSU

    Developing countries


    Sources:MOSUS data (, Schandl and Eisenmenger 2006, Maddison 2001.

    what fraction of the biomass that would have been available Analysis of Gobal Resource Extractionin the absence of land use – either foregone due to land use or harvested and thus diverted to human uses. Here the picture is As the overall picture is rather similar for material and considerably different from the material and energy flow data: energy flows, we give here only a more in-depth analysis of The industrial core contributes only 21 per cent to the global the resource extraction data. Figure 2 presents a highly total, east Europe and the FSU 12 per cent and the developing aggregated analysis of the resource extraction in the three countries 67 per cent. world regions. Domestic extraction refers to the total volume

    Table 1: The World Economy Around the Year 2000: Monetary and Biophysical Indicators

    Population Area GDP Per Capita GDP Resource Energy Use* HANPP** Extraction [Pentagrams [109 heads] [106 km2] [1012 $/yr] [103$/cap/yr] [109 tonnes/yr] [1018 joules/yr] carbon/year]

    Industrial core 0.838 32.0 18.0 21.5 19.9 268 2.78 E Europe, FSU 0.412 23.5 1.8 4.4 5.4 68 1.56 Developing countries 4.658 78.6 13.9 3.0 28.3 283 9.01 Total 5.908 134.1 33.7 5.7 53.6 618 13.35 Data year of [1998] [1998] [1998] [2000] [2000] [2000]

    Notes: * “Energetic metabolism” [Haberl 2001]; i e, including all biomass used by society. ** Excluding human-induced fires. All monetary values are 1990 international Geary-Khamis $.

    Sources: Maddison 2001; Schandl and Eisenmenger 2006;; Krausmann, et al 2006.

    Figure 3: Global Resource Extraction 1980-2002

    (a) Breakdown by Material Categories

    60 50 40 30 20 10 0 (Billion t/yr) 1980 1985 1990 1995 2000 Biomass MInerals Metal ores Fossil fuels

    (b) Breakdown by Regions

    60 50 40 30 20 10 0 (Billion t/yr) 1980 1985 1990 1995 2000 Developing countries E Europe and FSU Industrial core

    Data sources:

    of resources extracted on the territory of the respective aggregate of countries, accounted for as yearly mass flow (metric tonnes per year). Four broad categories of materials are distinguished. Biomass, that is, primarily plants harvested through agriculture or forestry – accounted for as fresh weight, with the exception of grazed biomass which is counted at a standardised water content of 14 per cent. The category “ores” includes ores and minerals used in industry. “Construction” stands for mineral resources used for construction purposes. And “fossil fuels” refers to crude oil, coal, lignite, peat and natural gas. The accounts exclude water except for the water content of the above-mentioned materials. Material flow data were taken from the literature [Schandl and Eisenmenger 2006,].

    Figure 2 analyses the global patterns in resource extraction. Note that not all of the resources extracted within one of the world regions are necessarily consumed there, as trade plays an increasing role (see next section). Because a consistent global database on domestic material consumption is at present unavailable, we have to use this database. Figure 2a reports data on the total volume of resources extracted, showing that biomass makes up a smaller part of the resource extraction in the industrial core and east Europe and the FSU, whereas it plays a larger role in the developing countries in relative terms. Figure 2b shows that this is so despite the fact that per capita biomass extraction is lower in the developing countries. But while the per capita extraction of biomass in the developing countries is only about half of that in the other two groups of countries, the per capita extraction of minerals, ores and fossil fuels is almost an order of magnitude smaller in the developing countries than in the industrial core – in line with the notion that the transition from agrarian to industrial metabolism is mainly based on “subterranean” resources [Sieferle 2001; Fischer-Kowalski and Haberl 2007], both in terms of materials and energy. Figure 2c reports data on the amount of resource extraction needed per unit of GDP produced, showing that the industrial core is able to generate much more GDP per unit of resource extraction than the other two world regions. East Europe and the FSU needs about three times more resources per unit of GDP and even surpasses the developing countries. In terms of resource extraction per unit area the industrial core is far above the global average and east Europe and the FSU far below the average, a fact mostly explained by the low population density of the latter group of countries.

    Land Use Intensity: A HANPP Perspective

    Table 2 gives a more in-depth analysis of global HANPP patterns. NPP0, the productivity of the potential vegetation – that is, the vegetation that would prevail in the absence of land use

    – is an indicator for natural biomass production capacity of a region or, if expressed per unit area, an indicator of fertility. Table 2 shows that NPP0 per unit area is almost identical in the industrial core and in east Europe and the FSU, whereas that of the developing countries – a group that also includes the tropical regions – is considerably higher. Total NPP0 per world region thus reflects mostly each region’s share of total land area, but also the higher potential productivity of the developing countries. HANPP aggregates two processes: (a) changes in productivity resulting from land use, here denoted as ΔNPPLC (productivity change resulting from land conversion) and

    (b) harvest of NPP (NPPh), a figure that includes not only harvest of commercial products (timber, grain, etc), but also felling losses, un-used by products such as straw, biomass grazed by livestock and similar items. A large ΔNPPLC value indicates that a region is not able to use the productive potential of its territory well, while small ΔNPPLC can be interpreted as a high

    Table 2: Breakdown of Global Human Appropriation (HANPP) ofNet Primary Production by World Regions

    Industrial East Developing Total
    Core Europe Countries
    and FSU
    NPP0 [Pg C/yr] 13.5 9.5 42.4 65.5
    NPPact [Pg C/yr] 12.6 8.5 38.2 59.2
    NPPh [Pg C/yr] 1.8 0.5 4.8 7.1
    NPPt [Pg C/yr] 10.7 8.0 33.3 52.0
    ΔNPPLC [Pg C/yr] 1.0 1.0 4.3 6.3
    ΔNPPLC% [%] 7.2% 11.0% 10.0% 9.6%
    HANPP* [Pg C/yr] 2.8 1.6 9.0 13.4
    HANPP%* [%] 20.5% 16.4% 21.2% 20.4%
    NPP0/area [gC/m2/yr] 427 424 533 490
    HANPP/area [gC/m2/yr] 88 69 113 100
    HANPP/cap [tC/cap/yr] 3.26 4.08 1.88 2.21
    HANPP/GDP [kgC/$] 0.152 0.937 0.627 0.389

    Notes: * excluding human-induced fires.

  • (i) For explanation of parameters in col 1, see text.
  • (ii) Pg C/year is pentagram of carbon/year.
  • Figure 4: Analysis of Global Resource Extraction Patterns Population density is obviously one important determinant

    (A) Resource Extraction Per Capita and Year of this pattern.

    Global Trajectories 1700-2000

    The previous section has shown that a biophysical view on humanity’s economic activities generates a picture that is con

    0,0 5,0 10,0 15,0 20,0 25,0 Industrial core E E urope and F S U D eveloping countries G lobal averageResources per capita (t/cap/yr)

    siderably different from the traditional “chrematistic” perspec

    tive. This section assembles available global time series data of biophysical flows associated with economic activities and relates

    them to population and GDP.

    Resource Extraction 1980-2002

    Data on global material flows are still very incomplete. Fully

    fledged material flow accounts (MFA) currently exist only for a selected group of countries, most of which belong to the industrial core [e g, Matthews et al 2000; Moriguchi 2002; Weisz et al 2006]. We here present resource extraction data (“domestic











    (B) Resource Extraction Per Unit of GDP


    Indus trial c ore E E urope and FS U Developing c ountries Global average
    1980 1982


    lished on the internet ( and cover only a relatively short period from 1980 to 2002. Figure 3


    extraction” in the above-discussed sense) that have been pub-

    Resources per GDP (t/1000$)

    summarises these data, showing that resource extraction grew

    considerably in this 20 year period (+36 per cent). Growth in


    biomass extraction was lowest (+28 per cent), whereas minerals


    (+40 per cent) and ore (+56 per cent) extraction grew faster than


    average resource extraction (Figure 3a). Resource extraction fell in east Europe and the FSU, while it grew slowly (+18 per cent) in the industrial core and rapidly in the developing countries,



    where resource extraction surged by 73 per cent from 17 billion t/yr in 1980 to almost 30 billion t/yr in 2002 (Figure 3b).

    Data are analysed in Figure 4. Figure 4a shows that per capita resource extraction is highest in the industrial core where it fluctuates around 22-23 t/cap/yr without a clear trend. In the


    Data Sources:Maddison 2001,










    efficiency of land use. Table 2 shows that the industrial core has the most efficient land use system, while east Europe and the FSU has the highest ΔNPPLC, if this indicator is expressed as a percentage of NPP0. Aggregate HANPP is similar in the industrial core and in the developing countries (around 21 per cent of NPP0; in absolute terms HANPP per unit area is higher in the developing countries as they are also potentially more productive) and lower in east Europe and the FSU. This has to do with the low population density (i e, abundance of land that is used very inefficiently). Per capita HANPP is highest in east Europe and FSU with over 4 tonnes of carbon per capita and year, whereas the developing countries are below 2 tonnes of carbon/cap/yr. HANPP per unit of GDP varies grossly, with the industrial countries at only 0.15 kg of carbon/$, whereas east Europe and the FSU use over 6 times as much HANPP per unit of GDP.

    Note that these three large aggregates are considerably variable in themselves. For example, the group of developing countries includes countries with extremely high HANPP values such as Bangladesh (75 per cent) or India (66 per cent), countries with intermediate values such as China (34 per cent) or Indonesia (23 per cent) as well as countries with very low HANPP (e g, many central African countries that are around 3-5 per cent). In the industrial core, HANPP may also be very high (e g, the Netherlands with 63 per cent, Denmark with 57 per cent), intermediate (e g, US with 30 per cent, Japan with 23 per cent) or low (e g, 11 per cent in Norway).

    developing countries, the domestic extraction of resources is growing steadily and slowly, but at a level that is four to five times lower. In east Europe and the FSU, resource extraction grew until the late 1980s and declined considerably after the fall of communism. Resource extraction per unit of GDP is by far lowest in the industrial core, followed by the developing countries. It declines throughout the whole period in the industrial core and in the developing countries, whereas the pattern in east Europe and the FSU is unstable. This may also have to do with the above-mentioned problems associated to the measurement of GDP (and probably also material flows) in these countries. It seems that east Europe and the FSU is the only region where no consistent decoupling trend between resource flows and GDP took place; today this is the region with the by far largest resource extraction per unit of GDP, while the level had been similar to that of the developing countries in 1980.

    Biomass and Energy: Towards a 300-Year Perspective

    In contrast to material flows, where data are currently restricted to extraction, high quality data are now available on global energy flows for the period 1930-2000, including full accounts of human use of biomass according to the above-mentioned principles for the time period of 1910-2000. Biomass data were derived from data published by the FAO and its predecessors [Krausmann et al 2006]. Data on fossil fuels, hydropower and

    Source:Krausmann et al 2006.

    nuclear energy were taken from conventional energy statistics, above all those published by the International Energy Association. Methods and concepts used are discussed elsewhere [Haberl 2001; Haberl et al 2006]. In the period from 1910-2000, world population rose by a factor of 3.4 from 1.8 to 6.0 billion people. Growth was strongest in the developing countries (factor 4.2) and much slower in the industrial core (2.2) and east Europe and the FSU (2.1).

    We start with an analysis of biomass consumption, here expressed as the energy content (gross calorific value) of the biomass used by humans. Figure 5a shows that the biomass consumption of the developing countries is rising strongly and continuously throughout the whole period, whereas biomass consumption of the industrial core and east Europe and the FSU rises only about two-fold and peaks in 1990 due to a reduction in biomass consumption in east Europe and the FSU. In order to put these data in perspective it is useful to note that the NPP0 value of 65.5 PgC/yr quoted above is approximately equivalent to an energy flow of over 2400 EJ/yr; the current NPP of the terrestrial biota is a bit below 2200 EJ/yr. The data presented

    Source:Krausmann et al 2006.

    in Figure 5a show, therefore, that humanity’s use of biomass has risen from about 3 per cent of the Earth’s potential productivity to over 9 per cent of that value, not counting biomass destroyed by human-induced fires and some other human-induced flows (e g, roots killed through cutting trees). This does, however, not imply that HANPP has risen three-fold: It seems likely that changes in agricultural technology, above all the so-called green revolution, have significantly raised the productivity of agroecosystems. HANPP data covering the whole period are, at present, unfortunately not available.

    The analysis of biomass flows per capita and year shows that the per capita consumption of biomass stays in a rather narrow range between 30 and 65 GJ/cap/yr in all regions throughout the whole period of time. Note that this is about 10-20 times the amount of biomass energy needed as food to adequately provide energy to support one individual human’s metabolism (about 3.5 GJ/cap/yr; see Boyden 1992). The data suggest that there seems to be an “industrial” consumption pattern pertinent in both the industrial core and east Europe and the FSU, characterised by a consumption level around 60 GJ/cap/yr, a high value

    l i i l 19201970198019902000 19101970198019902000 70 60 50 40 30 20 10 Gigajoules/capita/yearIndustrial core E Europe and FSU Developing countries Global average
    l 250 200 150 100 50 Exajoules/year Developing countries E Europe and FSU Industrial core




    Indus tria l co re E Eu rope and FS U D e ve lop ing co u n trie s G lobal avera g e 1930198019902000 Gigajoules/capita/year 300 250 200 150 100 50 1930198019902000
    D e ve lo p in g co u n trie s E E urope and FS U In du s trial co re 700 600 500 400 300 200 100 Exajoules/year

    (b) Per Capita

    (b) Per Capita Energy Flows


    Figure 5: Global Biomass Flows 1910-2000:Figure 6: Humanity’s Energetic Metabolism 1930-2000Apparent Consumption (Domestic Extraction Plus Import(a) Aggregate Energy FlowsMinus Export) of Biomass

    (a) Total

    Figure 7: Global Energetic Metabolism 1970-2000 amount of energy used in the industrial core in 1930 (around

    (a) Per Capita Domestic Energy Consumption

    150 GJ/cap/yr). In the industrial core, per capita energy use followed a logistic function and about doubled from around 150 GJ/cap/yr in 1930 to a bit lower than 300 GJ/cap/yr in 2000.

    East Europe and the FSU seemed to catch up to the level of

    energy use of the industrial core, but experienced a sharp decline

    Industrial core E Europe, FSU Developing countries Average 350 300 250 200 150 100 50 0Energy use per capita (GJ/capita/year)

    following the collapse of communism in the early 1990s.

    A global energy use time series for the last millennia has been

    constructed based on data on energy use [Podobnik 1999] and

    assumptions on per capita biomass use [Haberl 2006]. Based on the data presented in Figure 5 and elsewhere [Haberl et al 2006; Dearing et al 2006], we here reconstruct global energy use 17001910 and combine these data with those presented in Figure 6.

    The results are analysed in Figure 7 that shows per capita energy throughput in the global average for 1700-2000 and in the three groups of countries 1930-2000. Figure 7b shows that energy use per unit of GDP declines consistently in the global average as

    Industrial core E Europe, FSU Developing countries Average 20002000 90 80 70 60 50 40 30 20 10 0Energy use per unit of GDP (MJ/$)







    (b) Domestic Energy Consumption Per Unit of GDP

    well as in the three groups of countries, with the exception of

    east Europe and the FSU. The results for this group should,

    however, not be overinterpreted, because both GDP data and biophysical data are highly uncertain and, for much of the period covered in Figure 7, GDP data are not comparable to GDP data

    calculated using the usual, internationally agreed standards

    [Maddison 2005].

    Discussion and Conclusions

    Data on humanity’s economic activities in terms of both







    monetary and biophysical flows are only gradually becoming available. We have compiled the most recent data in this article in order to give a first, rough-and-ready integrated picture of the development of the world economy 1700-2000. The available database is still spotty and in many respects unsatisfactory, and it certainly seems warranted to voice caveats against over-interpretation of single data points. Further data work to corroborate and refine the results presented here is highly desirable (and under way). Nevertheless we believe that an overall picture is taking shape. We highlight three issues:

    (a) humanity’s role as a globally relevant biogeochemical force [Crutzen and Steffen 2003], (b) implications for future development scenarios, (c) implications for research, in particular for ecological economics.

    With respect to the first issue, we note that our data clearly show that humanity’s socio-economic metabolism has become a globally relevant component of the global biogeochemical flows, supporting the notion that we have entered a new geological era denoted by some as the “anthropocene” [Crutzen and Steffen 2003]. Humans consume about 10 per cent of the biomass produced each year in terrestrial ecosystems. In addition, humans have altered the biosphere’s productivity and introduced other changes that, taken together, result in a global human appropriation of NPP of around 22-23 per cent of total terrestrial NPP0 or around 30 per cent of aboveground terrestrial NPP0 [Krausmann et al 2006]. Meanwhile, human bodies account for nearly one-third of total global terrestrial vertebrate biomass and domesticated animals account for over two-thirds, whereas wild vertebrates make up only 3 per cent of the total [Smil 1991]. The large-scale combustion of fossil fuels releases around

    6.3 Pg C/yr to the atmosphere [Sabine et al 2004], thus contributing strongly to the rising CO2 content of the atmosphere, one of the most important drivers of global climate change.

    that probably results, among others, from a high level of consumption of animal protein. Note that consumption may be considerably higher in some countries. For example, the US consume around 90 GJ/cap/yr, and some sparsely populated countries such as Finland even more [Haberl et al 2006]. Biomass consumption dropped rapidly in east Europe and the FSU after the breakdown of communism. In contrast to that “industrial” pattern, the developing countries consume between 30 and 40 GJ/cap/yr. There, per capita consumption of biomass has declined from below 40 GJ/cap/yr in the first-half of the period under consideration to above 30 GJ/cap/yr in the period’s second-half.

    Total energy use is analysed in Figure 6, in which technical energy use was added to the biomass flows reported in Figure 5. “Technical energy” here refers to fossil fuels, hydropower and nuclear energy. Fossil fuels contribute most to this item (89 per cent in the year 2000). Figure 6a shows that aggregate energy use grew by a factor of 4.14 on the global average, but this growth was unevenly distributed around the globe: Both the industrial core and east Europe and the FSU grew by a factor of 3.7, whereas the developing countries grew by a factor of 4.9. That latter large growth was, however, mostly due to the rapid population growth of that region: per capita availability of energy grew only by a factor of 1.44 in the developing countries, a value not significantly different from the global average growth (1.46), whereas per capita energy use roughly doubled in both the industrial core and in east Europe and the FSU.

    Figure 6b shows that per capita energy use grew slowly but steadily in the developing countries, a group of countries that, however, never in the whole period came anywhere near the Ecological footprint calculations show similar trends [Wackernagel et al 2002].

    At the same time, around three quarters of humanity still live in poverty. At present, per capita GDP in the industrial core is over seven times higher than that in the developing countries, per capita resource extraction and energy use about five times higher. If we assume that the roughly three quarters of the world population that currently live in the developing countries would adopt the industrial consumption pattern this would be sufficient to raise humanity’s energy consumption to a level between 1800 EJ/yr (assuming a world population of 6 billion) and 2550 EJ/yr (based on a projected world population of

    8.5 billion around 2050; Lutz et al 2004). This amount of energy is roughly equal to the potential NPP of the Earth’s terrestrial biota. This simple thought experiment suggests that the developing countries will find it impossible to follow the trajectory the industrial core has followed in the last two centuries, for two reasons: First, the reserves of some of the fossil fuels will not be sufficient [e g, see the discussion about peak oil; Campbell 2004; Hallock et al 2004], and second, even if there is for a time enough natural gas and coal, the carbon emissions resulting from such a growth in fossil fuel combustion would probably result in disastrous effects from climate change, maybe also including runaway phenomena such as a dieback of tropical rainforests or a thawing of permafrost that would release enormous amounts of greenhouse gases [e g, Cox et al 2000; Friedlingstein et a 2003].

    Our findings corroborate the view [Haberl and Krausmann 2001] that efficiency increases in terms of a reduction in resource use per unit of GDP may be beneficial, but are certainly not sufficient to result in a reversal of current trends. For example, the data presented in Figure 7 show that the amount of energy required to produce a unit of GDP has fallen consistently in both the industrial core and the developing countries as well as in the global average. In other words, it rather seems to be the case that efficiency increases are rather fuelling GDP growth than helping to reduce aggregate resource consumption [Ayres and Warr 2005]. At least so far, efficiency increases are more than compensated by increases in consumption levels. Whether absolute dematerialisation – i e, a reduction in resource consumption in absolute terms in a period of GDP growth – can be achieved over longer periods of time is a question that still remains to be solved.

    With respect to future research directions, we feel that the results presented here suggest that (neo)classical economic concepts such as cost-benefit analysis of environmental policy instruments or the quantification and internalisation of “external costs” – although useful in many respects – will not be sufficient as a conceptual basis for sustainability science. We rather support the view that Ecological Economics and related approaches, in aiming to contribute economic expertise to the sustainability discourse, would benefit from a socioecological perspective that envisages sustainability as the goal to promote social well-being (or quality of life) and economic prosperity while at the same time avoiding to threaten vital ecological assets, functions, or services. In order to support this ambitious, and so far elusive, goal it will be necessary to complement and integrate monetary analysis with analyses of stocks and flows of vital biophysical resources such as materials and energy and the colonising interventions into living systems such as genes, organisms or ecosystems they entail. This will require the development of new, integrated models able to support a fundamental reorientation and the development of new development models that might eventually contribute to a transition towards sustainability.



    [This paper has been prepared for the ninth biennial conference “Ecological Sustainability and Human Well-Being”, International Society for Ecological Economics to be held in New Delhi, December 15-18, 2006 ( It is based on empirical work conducted in various projects funded, among others, by the Austrian Science Funds, the Austrian Federal Ministry of Education, Science and Culture (“Cultural Landscapes Research” and proVISION programmes) and by the European Union (projects MATISSE and ALTER-Net). The paper contributes to the Global Land Project ( Several colleagues have provided access to data and discussion, above all Nina Eisenmenger, Marina Fischer-Kowalski, Karl-Heinz Erb, Veronika Gaube.]


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