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Www.csiro.au Dynamic resilience in landscape exploitation systems Cameron Fletcher, David Hilbert, Andrew Higgins, Peter Roebeling, John Ludwig CSIRO Sustainable.

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Presentation on theme: "Www.csiro.au Dynamic resilience in landscape exploitation systems Cameron Fletcher, David Hilbert, Andrew Higgins, Peter Roebeling, John Ludwig CSIRO Sustainable."— Presentation transcript:

1 Dynamic resilience in landscape exploitation systems Cameron Fletcher, David Hilbert, Andrew Higgins, Peter Roebeling, John Ludwig CSIRO Sustainable Ecosystems CSIRO Complex Systems Science Emerging Science Area

2 Synopsis Important points  We have created a dynamic, generic model of landscape exploitation systems  We analyse the topology of state space to summarize properties across all systems  We aim to analyse these systems at multiple scales, across multiple objectives Definition  Landscape exploitation systems are systems in which human beings harvest a renewable natural resource using human-made capital to create an “economic” good. They are therefore very general, including hunting-gathering, swidden agriculture, grazing and intensive agriculture systems.

3 Outline Synopsis ► Motivation Predator-prey analogy Exploitation systems Model structure State space topology First results Multi-objective optimization A spatial mosaic

4 Motivation

5 Outline Synopsis Motivation ► Predator-prey analogy Exploitation systems Model structure State space topology First results Multi-objective optimization A spatial mosaic

6 The predator-prey analogy Population Time

7 A model exploitation system Natural capital Human-made capital Time Natural capital Human-made capital

8 Outline Synopsis Motivation Predator-prey analogy ► Exploitation systems Model structure State space topology First results Multi-objective optimization A spatial mosaic

9 A range of generic systems Hunting-gathering Natural capital: Edible rainforest plants Bush meat Human-made capital Human beings Bows and arrows etc. Swidden agriculture Natural capital: Rainforest nutrients Human-made capital Human beings Rudimentary tools Grazing system Natural capital: Native grasses Human-made capital Cattle, sheep Some industrial tools Intensive agriculture Natural capital: Some key soil nutrients Human-made capital Cultivated crop plants Tractors Industrial tools

10 Outline Synopsis Motivation Predator-prey analogy Exploitation systems ► Model structure State space topology First results Multi-objective optimization A spatial mosaic

11 The local model Natural capital growth=Intrinsic growth-Consumption Human-made capital growth=Reinvestment-Depreciation Earning a profit Creating production Exploiter- Manager Reinvestment Natural capital growth=Intrinsic growth-Consumption Human-made capital growth=f(Consumption)-Depreciation Consuming natural capital

12 The local model Intrinsic growthConsumption Savings rateDepreciationProduction

13 Making a choice Reinvestment=Savings FractionxProfit

14 Outline Synopsis Motivation Predator-prey analogy Exploitation systems Model structure ► State space topology First results Multi-objective optimization A spatial mosaic

15 Space-space topology Natural capital Human-made capital

16 Space-space topology Natural capital Human-made capital

17 Space-space topology Natural capital Human-made capital State space topology

18 Outline Synopsis Motivation Predator-prey analogy Exploitation systems Model structure State space topology ► First results Multi-objective optimization A spatial mosaic

19 First results – simple strategies 0.7 ???

20 Results Control parameterNatural capital Human-made capital Dynamics Economics Control parameterNatural capital Human-made capital Dynamics Economics Control parameterNatural capital Human-made capital Dynamics Economics Control parameterNatural capital Human-made capital Dynamics Economics

21 Results Control parameterNormalized performance Economic (solid), basin size (dashed) and return time (dotted) performance Control parameterNormalized performanceControl parameterNormalized performanceControl parameterNormalized performance

22 Outline Synopsis Motivation Predator-prey analogy Exploitation systems Model structure State space topology First results ► Multi-objective optimization A spatial mosaic

23 Control parameter Normalized performance Dynamic objective Economic objective Pareto front Multi-objective optimization  We can investigate dynamic qualities like resilience  We can investigate traditional measures like profits  Is there a formal way to combine out investigations of both?

24 Results – Multi-objective optimization Trade-offs between dynamic and economic performance Economic performance Dynamic performance Economic performance Dynamic performance Economic performance Dynamic performance Economic performance Dynamic performance

25 Outline Synopsis Motivation Predator-prey analogy Exploitation systems Model structure State space topology First results Multi-objective optimization ► A spatial mosaic

26 Spatial systems  Region built up of independent farms, with independent exploiters, each with their own management strategies and goals  Management strategies and goals are functions of economic and social forces across the region, and they change with time  How does the behaviour of the total system emerge from the many diverse local behaviours?

27 Pareto front Spatial systems and multi-scale optimization Multi-scale optimization  Across a spatial system, each exploiter will manage towards different optima  In addition, the global system will exert some pressure to find a “social optimum”  Can we capture this multi-scale optimization using the tools we have developed? Large-scale social (dynamic?) objective Local scale private (economic?) objective

28 Thank You CSIRO Sustainable Ecosystems NameCameron Fletcher TitleEcological Modeller Phone Webwww.csiro.au Contact CSIRO Phone Webwww.csiro.au CSIRO Sustainable Ecosystems NameDavid Hilbert TitleEcological Modeller Phone Webwww.csiro.au


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