As we begin to address global challenges such as climate change, peak oil and over-population it is becoming apparent that we must re-orientate our society towards lower energy availability. This means that in the future, we will need to live in a world where our resources are produced and accounted for much closer to home. We will need to begin to live within the long term carrying capacity of our landscapes.

A prototype Carrying Capacity Dashboard has been developed to estimate the productive capacity of the Australian landscape at various scales: national, state and regional.

The Dashboard allows you to test how many people the resources of a certain area may support as well as determining how various lifestyle choices can influence land-use requirements. You can assess options such as a population’s diet, agricultural techniques, energy usage and recycling practices to gain real-time results. This form of modelling can help determine optimal placement, size and configuration of future human settlement as well as promoting societal behaviour consistent with the limits imposed by the natural environment.

The Carrying Capacity Dashboard is a prototype only and is currently being developed by Murray Lane as part of his PhD at Queensland University of Technology. We value your feedback on the Dashboard, and also your contribution to the Carrying Capacity Blog below.

Aims of the Carrying Capacity Dashboard

In its broadest sense, research around the Carrying Capacity Dashboard aims to highlight how society’s understanding of constraints to the productive capacity of its resource base is vital to its long-term survival. A growing mainstream awareness in the importance of linking a population to the carrying capacity of its landscape has to date, largely been rhetorically rather than empirically tackled. For instance, while both the Redlands City[i] and Sunshine Coast Regional Councils[ii] have publicly committed to living within their carrying capacities, they don’t currently have the tools to determine the actual extent of these limits.

This research aims to identify, examine and compare existing approaches to carrying capacity assessment and consider their relevance to future spatial and infrastructure planning. It raises the following questions: Which carrying capacity assessment models are best suited for determining future sustainable land-use and community infrastructure? What gaps in existing research need to be addressed? Is it possible to achieve a practical model for assessing regional human carrying capacity?

This research aims to add practical application to what are currently well-intentioned but untested emerging societal aspirations concerning carrying capacity assessment. Basic questions such as, “How much land does a population require for its minimum resource requirements?” are currently not easily measurable. It is anticipated that the carrying capacity model developed through this research, can more accurately define the variables inherent in this question, and more clearly articulate possible outcomes. For example, the model might suggest that a certain region’s population may currently be within the carrying capacity of its landscape for one year of average production given existing consumption patterns, but perhaps it may be over-capacity if longer timeframes or different consumption patterns are applied. Carrying capacity assessment thus offers a dynamic tool for ascertaining population thresholds and potential future population distributions, as well as providing important guidelines for living within these physical limits. As such, it has the potential to influence urban and rural planning policy at all levels of government. It can also be useful for researchers and educators in highlighting system boundaries and physical limits to design proposals. Perhaps above all else, it can help individuals and local communities to more clearly define lifestyle changes necessary to ensure more resilient and sustainable societies in the future.

One productive outcome of this research is to develop an easily accessible carrying capacity model, the Carrying Capacity Dashboard, in order to better define and publicise how the process of carrying capacity modelling can operate and to give users a real experience of testing various carrying capacity parameters. Carrying capacity analyses, by definition, are reflective of a particular piece of land at a particular time, which invariably possesses its own unique physical characteristics, resources and environmental responsiveness. Consequently, the model generated as part of this research aims to estimate maximum population thresholds based on the unique biophysical characteristics of specific geographical regions within Australia. The model may account for various societal and agricultural systems, environmental protection processes and a range of lifestyle choices such as energy, water and food consumption. Given the complexity of the input data, a definitive carrying capacity population number is never likely to be achievable. However, it is possible to offer an approximate figure or range of figures as long as the variables are clearly articulated at the same time. For example, it may be possible to state that the Southeast Queensland region has a carrying capacity of say, two hundred thousand people, assuming that they ate a certain diet and farmed a certain way. The advantage of this approach is that these variables can also be dynamically altered and the impacts on carrying capacity observed.

This research primarily aims to explore quantitative approaches to carrying capacity assessment, using mathematical formulae to generate a numeric result.[iii] Given the difficulties of incorporating wide ranging and ever-changing variables, it is acknowledged that the measurement of carrying capacity is a complex task. In fact Livi-Bacci[iv] argues that, “the identification of carrying capacity presents so many conceptual difficulties as to be virtually useless for practical purposes.” However, there already exist several workable examples of carrying capacity assessment models so in disproving Livi-Bacci’s assertions, the objective of this research is to synthesise and refine these methodologies into an approach suitable for practical purposes. In summary, the processes proposed for this research involve refining existing carrying capacity assessment methodologies, compiling existing data, constructing the model, testing it and publicising it.

There are two key steps that populations must take in order to live within their long-term bio-regional limits - carrying capacity assessment and maintenance. It thus follows that the scope of this research is bound by these twin aspects. From an assessment perspective, populations need to make ongoing assessments of both their landscapes capabilities and societal needs; and a fair and sustainable balance must be struck. Secondly, populations need to maintain a size which is far enough below the carrying capacity of regional biophysical limits to allow for productive variability from year to year. The implications for carrying capacity maintenance range from migration to birth control to re-localisation.

From a land-use planning perspective, the scope of this research includes all the systems involved in the way we interact with our environment. As such, it comprises a range of settings such as urban, rural and environmental planning; as well as societal systems that underpin our society such as governance and the economy. While the relationship between the land and its people already forms the basis for existing land-use planning, a carrying capacity focus also offers a way to better measure the relationships between these aspects. In fact, it is suggested that the assessment of these biophysical constraints should form the first step in future land-use planning practice. The practical steps involved in this process of carrying capacity assessment involve quantifying these constraints, analysing them collectively, and then making predictions about their behaviour.

The success and validity of future land-use planning necessitates the inclusion of whole systems carrying capacity assessment models estimating the ability of a landscape to produce the resources necessary for a certain population as well as its capacity to assimilate any subsequent waste. However, a thorough incorporation of these dual components is ultimately beyond the scope of this research. The focus, therefore, has been largely on the first stage of a society’s resource utilisation, its resource production. This research argues that in a closed system (which carrying capacity assessment implies) there is a linear progression from resource production to resource usage (consumption) to resource assimilation (waste) so notwithstanding extreme environmentally destructive behaviour, the amount of resource assimilation is dictated by the amount of resources produced. Dilworth[v] explains this predicament another way by pointing out that society’s, “quantity of waste cannot be reduced without reducing the quantity of materials used.” This is not to suggest that the assimilation of waste is unlikely to have an impact on the carrying capacity of a given landscape; and it also does not mean to imply that a circular pattern of resource utilisation, where waste is recycled back into resource productivity, is not preferable to an entirely linear one. Rather, it merely observes that in a closed system, the degree of resource wastage, destined for environmental assimilation, is largely dependant on the degree of resource production, so is deemed to be of secondary importance.

[i] REDLAND CITY COUNCIL (2010) Redlands 2030 Community Plan.
[ii] GARDINER, P. (2009) Both sides say use it or lose it. Noosa News. Noosa News.
[iii] Quantitative assessment involves numeric calculations whereas qualitative analysis relies on theoretical formula (such as I=PAT) to illustrate carrying capacity concepts.
[iv] LIVI-BACCI, M. (1992) A Concise History of World Population, Oxford, Blackwell.
[v] DILWORTH, C. (2010) Too smart for our own good: the ecological predicament of humankind, Cambridge, Cambridge University Press.

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