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

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.

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

Motivation

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

The predator-prey analogy Population Time

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

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

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

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

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

The local model Intrinsic growthConsumption Savings rateDepreciationProduction

Making a choice Reinvestment=Savings FractionxProfit

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

Space-space topology Natural capital Human-made capital

Space-space topology Natural capital Human-made capital

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

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

First results – simple strategies 0.7 ???

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

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

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

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?

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

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

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?

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

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