The CSIRO Ocean Futures project uses several approaches to imagine the future, including: (i) models, (ii) foresights, and (iii) expert-based methods (superforecasting), and also draws on (iv) workshops and surveys, and (v) historical analyses.

Perhaps most troubling, we found an Intelligence Community in which analysts have a difficult time stating their assumptions up front, explicitly explaining their logic, and, in the end, identifying unambiguously for policymakers what they do not know.”

“… the importance of good analysis goes beyond accuracy. Decision makers need to understand the reasoning behind good conclusions, including what alternative explanations were considered, what assumptions were made, how evidence was evaluated, and how confident analysts are in their findings”.

1. Qualitative and quantitative modelling

Models can shed light on the technological, environmental and policy implications of coming changes or regulatory decisions

Models are an excellent means of synthesizing information and understanding. This can then enable prioritization regarding (i) collection of additional information and (ii) additional research.  Models also have an important role in planning for the future, where conditions may depart from those experienced in the past, a range of options are possible, and goals can vary.

Even when people agree on the broad goals, describing the details can lead to tensions given competing or conflicting objectives. Some of this tension comes from the flawed assumption that we all share the same mental model of how the world works. A tangible model can focus discussion and alleviate frustration.

Our modelling approaches may never capture all the uncertainty and surprises of the future, but they can provide insights on the strengths, weaknesses and unintended consequences of proposed actions and alternative futures. We use a range of tools from qualitative to quantitative, covering single species, entire biological communities, and the human system that relies on the ocean.

In our “futures” work, we recognize that humans instinctively use mental models to guide themselves through their daily tasks and make long-term decisions. We seek to build on these mental concepts of the way the world works. Internal rigour is added by a formal, often mathematical, framework – making sure that the logic and internal dynamics are consistent. Our models can tested under alternative assumptions around driving forces (e.g. economic demand, climate change) to see how different futures might unfold. This model-based approach to informing decision-making has long been used in natural resource management such as fisheries and forestry, and we seek to build on this foundation.

2. Foresighting

The Ocean Futures team uses foresighting approaches to develop our own skills, as well as prepare for alternative marine futures.

Foresighting” is a term associated with “Future Studies” to describe activities such as:

  • critical thinking concerning long-term developments,
  • debate and effort to create wider participatory democracy,
  • shaping the future, especially by influencing public policy.

Foresighting draws on approaches used in long-range and strategic planning, horizontal policy making and democratic planning, and participatory futures studies. Many of the methods that are commonly associated with Foresight (e.g. Delphi surveys, scenario workshops, etc.) – are based on approaches in the Futures field. Foresight is concerned with futures that are usually at least 5-10 years away and is action-oriented (the planning link) and thus will rarely consider perspectives beyond a few decades (though in areas such as marine spatial planning, or major marine infrastructure decisions are concerned, the planning horizon may be longer). We examine alternative pathways, not just what is currently believed to be the most likely future. Foresighting exercises may lead to development of multiple scenarios. These may be an interim step on the way to creating positive visions, success scenarios, and aspirational futures for marine systems.

3. Super-forecasting

Super-forecasting (SF) is an example of an expert-based method for investigating the future. The rationale for including a super-forecasting element in the project includes i) the belief that better forecasting leads to better decision making and ii) the empirical results that “… forecasts can be improved with behavioural interventions“ (Mellers et al., 2014). In particular, the SF literature suggests that forecasting skills can be improved by

  1. training, to address well-known cognitive biases
  2. teaming, to encourage sharing information and discussing the rationales behind the forecast
  3. tracking the forecasters performance, used as feedback for learning and
  4. elite teaming: placing the highest performers in elite teams.

An alternative set of instructions (the HABIT) to improve forecasting skills is included in the Hybrid Forecast Competition (HFC) training material:

  1. Hunt for the right information
  2. Answer the questions (poor forecasters answer the wrong question)
  3. Base rate awareness (inside vs outside view; the outside view sees a question as an instance of a wider set of questions)
  4. Inferring wisely (combine consistent and inconsistent evidence)
  5. Tracking news and adjust your forecast (belief updating by small frequent adjustment was the strongest mark of accurate forecasts)

We have investigated these approaches

  • To understand the super-forecasting literature and its potential value to O&A
  • to get some hand-on experience with this approach (how to set it up, run it, monitor it and evaluate it) and
  • to train the project team members in carrying out a forecasting activity.

Outcomes of this project include:

  • a better understanding of the forecasting process.
  • The development of a software platform designed for forecasting exercises
  • the comparison between forecasting and foresighting activities
  • an appreciation of the potential benefits and challenges involved in porting the learning to decision-makers and stakeholders as a part of an OF outreach process.

In addition, we also use and undertake


4. Historical Data Analysis

Insight into the future can be gleaned from an understanding of the past. Historical data, such as catch data, can be used to calibrate models (e.g. ecosystem models) that are in turn used to forecast possible futures. The Ocean Futures team has assembled a database of Australian historical catch data that is available for use.

This database consists of Australian commonwealth and state catch records, by species for a wide range of fisheries. Information in the annual Australian Fisheries Statistics, published by ABARES these reports provide detailed production, fishery profiles and gear, employment and trade data in this series since 1991. Prior to that the annual Commonwealth Australian Bureau of Statistics provide statistical information from Federation in 1901 to the present, including data on the volume and value of production from state and Commonwealth fisheries. They also provide data on the volume and value of Australian fisheries trade (export/imports) by destination, source and product;  profiles of Commonwealth and state fisheries and state aquaculture covering selected species, fishing method and number of license holders is also covered; employment; fisheries revenue and post-harvest information.

Useful reading

  1. Lotze, H. K. and B. Worm (2009). Historical baselines for large marine animals. Trends in Ecology and Evolution 24(5): 254-262.
  2. Peck, M. A., C. Arvanitidis, M. Butensch€on, D. M. Canu, E. Chatzinikolaou, A. Cucco, P. Domenici, J. A. Fernandes, L. Gasche, K. B. Huebert, M. Hufnagl, M. C. Jones, A. Kempf, F. Keyl, M. Maar, S. Mahevas, P. Marchal, D. Nicolas, J. K. Pinnegar, E. Rivot, S. Rochette, A. F. Sell, M. Sinerchia, C. Solidoro, P. J. Somerfield, L. R. Teal, M. Travers-Trolet and K. E. v. d. Wolfshaar (2016). Projecting changes in the distribution and productivity of living marine resources: A critical review of the suite of modelling approaches used in the large European project VECTORS. Estuarine, Coastal and Shelf Sciences:

5. Workshops and Surveys

Insight into perspectives and expectations from different stakeholder groups is critical in understanding and projecting alternative futures. For example, our team surveyed recreational fishers to explore how they might adapt to changes (van Putten et al. 2017).  Workshops and surveys can be used to gather information and develop conceptual models. They have also been used to

  • explore the views of society about the year 2050 (see 2050 Focus Group Feedback_v2), based on workshops in Hobart, Melbourne and Canberra in 2012 and 2013 (see also (Boschetti et al., 2014)).
  • Study the general attitudes towards in the future in the Australian population (Boschetti et al., 2016b)
  • Study the consistency of mental models of climate change in relation to climate policy choices (Richert et al., 2017)
  • Study the Australian citizens’ perception of the future resilience of Australian cities (Boschetti et al., 2016a)


  1. Boschetti, F., Fulton, E., Grigg, N., 2014. Citizens’ Views of Australia’s Future to 2050. Sustainability 7, 222-247.
  2. Boschetti, F., Gaffier, C., Price, J., 2016a. Citizens’ Perception of the Resilience of Australian cities. Sustainability Science submitted.
  3. Boschetti, F., Price, J., Walker, I., 2016b. Myths of the future and scenario archetypes. Technological Forecasting and Social Change 111, 76-85.
  4. Richert, C., Boschetti, F., Walker, I., Price, J., Grigg, N., 2017. Testing the consistency between goals and policies for sustainable development: mental models of how the world works today are inconsistent with mental models of how the world will work in the future. Sustainability Science 12, 45-64.
  5. van Putten, I. E., S. Jennings, A. J. Hobday, R. H. Bustamante, L. X. C. Dutra, S. Frusher, E. A. Fulton, M. Haward, E. É. Plagányi, L. Thomas and G. Pecl (2017). Recreational fishing in a time of rapid ocean change. Marine Policy 76: 167-177