Carrying capacity assessment estimates the maximum number of people that an area of land can support. A satisfactory carrying capacity model would thus need to encapsulate sufficient aspects of land-usage that impinge on population maximums. This section looks at various carrying capacity assessment models and considers their scale of analysis as well as the insights that they have provided.
Within carrying capacity literature, minor variations exist in the manner to best arrange the physical and sociological components of a carrying capacity model, but generally, they encapsulate similar fundamentals. For example, Fearnside[5] cites population, a particular area, environmental degradation plus a combination of technology and consumptive habits; House and Williams[6] propose resource production, environmental assimilation, infrastructure delivery and quality of life concerns; Thurow[7] profers production, consumption, egalitarianism and social discipline; while Hardin[8] reduces resources and lifestyle to a concept of cultural carrying capacity. Despite these differences, most authors define the limits to population by either their required inputs or subsequent outputs. Whether these inputs and outputs are culturally, technologically, economically or physically determined, they still form the basic determinants of carrying capacity. So, in essence, resources form the limiting factor on the input or supply side of the equation while environmental impacts form the opposing carrying capacity barrier on the output side. The population is wedged between these barriers but can alter the demands of each by collectively altering its behaviour.
An assessment of current carrying capacity literature suggests that methodologies can be categorised into approaches that focus more or less on the various components of a basic carrying capacity model (Figure 11). These elements include global boundaries, local boundaries, resources, population and impacts. Ultimately global limits form the outermost boundary for humanity’s carrying capacity. However, this level of analysis may not be the most appropriate scale for measuring population carrying capacity. Many authors subscribe to more localised boundary delineation within which to define smaller populations.
Figure 11. Carrying capacity modelling can be encapsulated in a simple input-output diagram. Resource inputs and impact outputs are positioned both within local and global boundaries as they can potentially occur at both scales. As Durham[10] points out, “[l]imits exist in both the resource and sink functions of the environment.”
All populations require physical inputs or resources to survive including energy, food, water and materials for shelter. The collection, production and utilisation of these resources rely on a certain area of land for the population in question. The boundary encircling these resources can be local and/or global. The utilisation of resources by a population is also likely to lead to certain physical outputs within either a global or local land area. These outputs may include environmental effects, waste products and climate change. In the case of carrying capacity assessment these outputs are likely to either enhance or, more likely, reduce carrying capacity, so could be viewed as impacts.
Five carrying capacity assessment typologies are thus identified: global, local (impacts derived), local (population derived), local (resources derived) and local (whole system derived). Even though international trade currently facilitates resource utilisation often at the global scale there are compelling reasons to also evaluate carrying capacity at a much smaller scale. In an energy-constrained future society, a more localised mode of production and consumption is likely to provide a more reliable source of essential resources with less reliance on long-distance transport. For example, local production of heavy and frequently used goods such as food would save a great deal on transportation energy costs. Gutteridge[12] concurs that, “the transfer of goods, the dumping of wastes or other forms of disturbance that may impact on Earth’s natural capital, and crucially its productive potential, must be considered if government policy is to aim society toward sustainability. Hence, transportation or the reduction thereof, is a crucial component of sustainability even though it has traditionally not been considered a high priority issue in the environmental or sustainability discourse.”
Global carrying capacity assessment models
A globally-derived carrying capacity assessment model assesses the ability of the entire planet to support the global population, incorporating resource supplies, societal demands and environmental impact capabilities (Figure 12). Given that our present system of resource utilisation is generally global in nature, this scale of analysis is actually the only typology truly representative of current circumstances. However, the sheer size of a global carrying capacity analysis makes it problematic, if not impossible, certainly with existing land-use data. Nevertheless, Joel Cohen[13] lists no fewer than 50 examples, displaying various degrees of sophistication and credibility, which have derived global population capacity estimates ranging from half a billion to one trillion people.
Figure 12. A global-focused carrying capacity model without a local boundary. Each component of this input-output process potentially affects the carrying capacity of the global sphere.
Two other globally-focussed forms of analysis, the Limits to Growth[14] and Ecological Footprint[15] models, exhibit informative characteristics without directly aiming to measure global carrying capacity. While their global focus helps to illuminate current population crises, it can also serve as a weakness, when, for example, localised responses to any such crisis may require detailed regional analysis. For instance, without the collection of data on the productive potential for localised areas, it is impossible to suggest an appropriate localised re-distribution of the population or any alterations in land-use practise or changes in diet that might optimise carrying capacity.
Limits to Growth
Over the last forty years, a group of scientists (principally Meadows, Meadows, and Randers) commissioned by an international think-tank, the Club of Rome, have produced a series of books on the Limits to Growth[17] investigating the trajectory of modern society. Their system dynamics computer model, World3, was developed to, “understand the broad sweep of the future - the possible modes, or behaviour patterns, through which the human economy will interact with the carrying capacity of the planet over the coming century.”[18] While this model did not specifically derive a global carrying capacity estimate, the very process adopted meant that their modelling explored the limits to global population, and hence, obliquely at least, its carrying capacity.
The results of World3 predictions are largely indicative rather than quantitative.[19] For example, projections are typically illustrated by graphs depicting a timeframe on the x-axis but an indeterminate scale on the y-axis (figure 13). Consequently, the rise and fall of various production and consumption parameters in relation to each other is more important than their actual amounts. As such, one valuable aspect that Meadows et al. brought to carrying capacity modelling was the integration of feedback mechanisms. For example, food production, industrial output, pollution, resource depletion and global population were all interconnected in their model, where any change in one of these societal parameters would have an equivalent impact on another.
Figure 13. Limits to Growth modelling[20] showing inter-relationships between global production and consumption parameters.
Even in 1972, projections produced by World3[21] showed a tendency towards future human population collapse and Meadows et al.[22] have since discounted the likelihood of a smooth levelling off of population in accord with either the Verhulstian logistic growth curve (figure 4) or current UN projections (figure 5). They argue that in order for a population to gradually reduce its growth rate as it approaches its carrying capacity, as per the logistic curve, it needs to act promptly to the accurate and timely signals of system limits such as resource availability and pollution impacts. They argue that in the absence of this timely adjustment, the trajectory of human population is likely to either be one of overshoot and oscillation or overshoot and collapse (figure 14). In both cases, the carrying capacity of the global environment is degraded but collapse occurs when severe and long-term degradation is apparent. Given the lack of global attention given to various environmental indicators and the interconnectedness of various societal parameters leading to feedback loops which exacerbate negative consequences, according to the World3 model the most likely outcome is overshoot and collapse.[23]
Figure 14: Meadows et al.[24] variations on how populations in overshoot might realign with its carrying capacity. Left: Oscillating equilibrium. Right: Collapse.
While the Limits to Growth modelling has received some criticism,[25] other authors such as Bardi[26] and Turner[27] have compared the original projections with actual data from the past 40 years and have found that so far, their predictions are reasonably accurate. While the World3 model highlights general trends, its relevance to carrying capacity modelling is limited. Some global carrying capacity analysis was conducted in later versions of their modelling, but according to Meadows et al.[28] these estimates were derived largely from another modelling approach, Ecological Footprint analysis.
[5] (Fearnside 1986, p.73) Fearnside, P., Human carrying capacity of the Brazilian rainforest. 1986, New York: Columbia University Press.
[6] (Cohen 1995, p.419) Cohen, J., How Many People Can the Earth Support? 1995, New York: W. W. Norton.
[7] (Thurow as per Cohen 1995, p.420)
[8] (Hardin 1986) Hardin, G., Cultural carrying capacity - a biological approach to human problems - AIBS News. BioScience, 1986. 36(9): p. 599-606.
[10] (Durham 1991, p.119) Durham, D.F., Notes on “carrying capacity”. Population & Environment, 1991. 13(2): p. 119-120.
[12] (Gutteridge 2005, p.33) Gutteridge, M., Ecological footprint and carrying capacity studies of South East Queensland: a comparison and discussion of results. 2005, Department of Natural Resources and Mines, Queensland Government: Brisbane.
[13] (Cohen 1995, p.402) The majority of estimates were between four and 16 billon, (Cohen 1995, p.214) suggesting that estimates nearing one trillion might be less than credible.
[14] (Meadows et al. 1972) Meadows, D.H., et al., The Limits of Growth. A Report for The Club of Rome's Project on the Predicament of Mankind. 1972, London: Pan.
[15] (Rees 1992) Rees, W., Ecological Footprints and appropriated carrying capacity: what urban economics leaves out. Environment and Urbanization, 1992. 4(2): p. 121-130.
[17] (Meadows et al. 1972; Meadows, Meadows, and Randers 1992; Meadows, Randers, and Meadows 2004)
[18] (Meadows, Randers, and Meadows 2004, p.137)
[19] Meadows et al. (1972, p.93) state that their graphs are, “not exact predictions of the values of the variables at any particular year in the future.”
[20] (Meadows, Randers, and Meadows 2004, p.169) Meadows, D.H., J. Randers, and D.L. Meadows, Limits to growth: the 30-year update. 2004, Vermont: Chelsea Green Publishing.
[21] (Meadows et al. 1972, p.124)
[22] (Meadows, Randers, and Meadows 2004, p.139)
[23] (Meadows, Randers, and Meadows 2004, p.167)
[24] (Meadows, Randers, and Meadows 2005, p.158 Meadows, D.H., J. Randers, and D.L. Meadows, Limits to growth: the 30-year update. 2005, London: Earthscan.
[25] Bardi (2011, p.2) cites various critics
[26] (Bardi 2011, p.2) Bardi, U., The Limits to Growth Revisited. 2011, New York: Springer.
[27] (Turner 2008, p.37) Turner, G., A Comparison of the Limits to Growth with Thirty Years of Reality, in Socio-Economics and the Environment in Discussion Working Paper Series 2008-9. 2008, CSIRO: Canberra.
[28] (Meadows, Randers, and Meadows 2005, p.291)
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