Modelling Human-Environment Interactions: Theories and Tools

1. Vespucci Summer School 2010 Modelling Human-Environment Interactions: Theories and Tools Gilberto Câmara Licence: CreativeCommons ̶̶̶̶ ByAttribution ̶̶̶̶ NonCommercial ̶̶̶̶ ShareAlike http://creativecommons.org/licenses/by-nc-sa/2.5/

2. By the Year 2050… 9 billion people: 6 billion tons of GHG and 60 million tons of urban pollutants. Resource-hungry: We will withdraw 30% of available fresh water. Risky living: 80% urban areas, 25% near earthquake faults, 2% in coast lines less than 1 m above sea level.

3. The fundamental question of our time How is the Earth’s environment changing, and what are the consequences for human civilization? fonte: IGBP

5. from Jackie McGlade (EEA)

6. Can we avoid that this…. Source: Carlos Nobre (INPE)

7. Fire... ….becomes this? Source: Carlos Nobre (INPE)

8. source: Global Land Project Science Plan (IGBP)

9. Global Land Project • What are the drivers and dynamics of variability and change in terrestrial human-environment systems? • How is the provision of environmental goods and services affected by changes in terrestrial human-environment systems? • What are the characteristics and dynamics of vulnerability in terrestrial human-environment systems?

10. Impacts of global land change More vulnerable communities are those most at risk

11. Human actions and global change photo: C. Nobre Global Change Where are changes taking place? How much change is happening? Who is being impacted by the change? What is causing change? photo: A. Reenberg

12. ~230 scenes Landsat/year Deforestation in Amazonia

13. What is a Model? Deforestation in Amazonia in 2020? simplified representation of a process Model = entities+ relations+ attributes+ rules

14. Computational models • Connect expertise from different fields • Make the different conceptions explicit If (... ? ) then ... Desforestation?

15. Computational models • Connect expertise from different fields • Make the different conceptions explicit Territory (Geography) Money (Economy) Culture (Antropology) Modelling (GIScience)

16. Modelling and Public Policy External Influences System Ecology Economy Politics Desired System State Decision Maker Scenarios Policy Options

17. Earth as a system

18. images: USGS Slides from LANDSAT Modelling Human-Environment Interactions How do we decide on the use of natural resources? Can we describe and predict changes resulting from human decisions? What computational tools are needed to model human-environment decision making? Aral Sea 1973 1987 2000

19. We need spatially explicit models to understand human-environment interactions Nature: Physical equations Describe processes Society: Decisions on how to Use Earth´s resources

20. Dynamic Spatial Models f (It) f (It+1) f (It+2) f ( It+n ) F F . . “A dynamical spatial model is a computational representation of a real-world process where a location on the earth’s surface changes in response to variations on external and internal dynamics” (Peter Burrough)

21. Forecast tp + 10 Calibration Calibration Dynamic Spatial Models tp - 20 tp - 10 tp Source: Cláudia Almeida

22. Which is the better model?

23. Limits for Models Uncertainty on basic equations Social and Economic Systems Quantum Gravity Particle Physics Living Systems Global Change Hydrological Models Chemical Reactions Meteorology Solar System Dynamics Complexity of the phenomenon source: John Barrow (after David Ruelle)

24. Soybeans Ranchers Small-scale Farming How do we decide on the use of natural resources? Loggers Competition for Space Source: Dan Nepstad (Woods Hole)

25. Human-enviromental systems [Ostrom, Science, 2005]

26. Types of goods Source: E Ostrom (2005)

27. Farms Settlements 10 to 20 anos RecentSettlements (lessthan 4 years) Old Settlements (more than 20 years) Source: Escada, 2003 Institutional analysis Identifydifferentactorsandtry to modeltheiractions

28. Institutional arrangements in Amazonia

29. Question #1 for human-environmentmodels What ontological kinds (data types) are required for human-environment models? Fields Cells (objects)

30. Concepts for spatial dynamical models Events and processes Resilience

31. Concepts for spatial dynamical models vulnerability degradation

32. Concepts for spatialdynamicalmodels biodiversity sustainability and much more… Human-environmental models need to describe complex concepts (and store their attributes in a database)

33. Question #2 for human-environment models Whatmodels are needed to describehumanactions?

34. Clouds: statistical distributions Clocks, clouds or ants? Clocks: deterministic equations Ants: emerging behaviour

35. Statistics: Humans as clouds y=a0 + a1x1 + a2x2 + ... +aixi +E Establishes statistical relationship with variables that are related to the phenomena under study Basic hypothesis: stationary processes Example: CLUE Model (University of Wageningen) Fonte: Verburg et al, Env. Man., Vol. 30, No. 3, pp. 391–405

36. Spatially-explicit LUCC models • Explain past changes, through the identification of determining factors of land use change; • Envision which changes will happen, and their intensity, location and time; • Assess how choices in public policy can influence change, by building different scenarios considering different policy options.

37. What Drives Tropical Deforestation? % of the cases  5% 10% 50% Underlying Factors driving proximate causes Causative interlinkages at proximate/underlying levels Internal drivers *If less than 5%of cases, not depicted here. source:Geist &Lambin (Université Louvain)

38. Driving factors of change (deforestation) source: Aguiar (2006)

39. W is the spatial weights matrix, • the productWY expresses the spatial dependence on Y (neighbors), •  is the spatial autoregressive coefficient. Linear and spatial lag regression models where: Y is an (n x 1) vector of observations on a dependent variable taken at each of n locations, X is an (n x k) matrix of exogenous variables,  is an (k x 1) vector of parameters (estimated regression coefficients), and  is (n x 1) an vector of disturbances.

40. Statistics: Humans as clouds source: Aguiar (2006) Statistical analysis of deforestation

41. CLUE modeling framework 100 x 100 km2 100 x 100 km2 25 x 25 km2

42. Construction of alternative models for each group/partition/ land-use Alternative CLUE runs 1997 to 2020 Comparison to real data and new frontiers process knowledge Scenario exploration: linking to process knowledge Cellular database construction Manaus- Boa Vista Santarém Porto Velho- Manaus São Felix/ Iriri Humaitá Apuí BR 163 Cuiabá-Santarém Boca do Acre Exploratory analysis and selection of subset of variables Aripuanã Scenario exploration

43. Scenarios for deforestation in Amazonia (2020)

44. Agent: flexible, interacting and autonomous Agents as basis for complex systems An agent is any actor within an environment, any entity that can affect itself, the environment and other agents.

45. Representations Communication Communication Action Perception Environment Agent-Based Modelling Goal source: Nigel Gilbert

46. Agents: autonomy, flexibility, interaction Synchronization of fireflies

47. Bird Flocking No central authority: Eachbirdreacts to its neighbour Notpossible to modeltheflock in a global manner. Need to necessaryto simulatethe INTERACTION betweentheindividuals

48. Requirement #2 for human-environment models Modelsneed to supportbothstatisticalrelations (clouds) andagents (ants)

49. Question #3 for human-environmentmodels What types of spatial relations exist in nature-society models?

50. Natural space is (usually) isotropic Societal space is mostly anisotropic 1975 1986 Rondonia