Spatial analysis for integrated natural resources management and decision making. Introduction. Topics. Keywords

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1 2008 European Summer School in Resource and Environmental Economics SPACE IN UNIFIED MODELS OF ECONOMY AND ECOLOGY for integrated natural resources management and decision making Carlo Giupponi, DSE-CEEM PhD Programme on Science and Management of Climate Change Euro-Mediterranean Centre for Climate Change Fondazione Eni Enrico Mattei Introduction 2008 European Summer School in Resource and Environmental Economics Topics Keywords Introduction Management of natural resource in socioecosystems of natural vs. human variables Integration of ecologic and socio-economic variables: the case of environmental assessment of agricultural systems Various approaches for supporting policy/decision making: cartographic models; spatial dynamic models; spatial decision support systems Assessing the past or the present, vs. projecting into the future: scenario analysis in the climate change context Introduction policy/decision making space social-ecological systems integration communication participation multiple criteria decision support 3 4 Unprecedented change in structure and functions Patterns of change More land was converted to cropland in the 30 years after 950 than in the 50 years between 700 and 850. Ecosystems in some regions are returning to conditions similar to their pre-conversion states Rates of ecosystem conversion remain high or are increasing for specific ecosystems and regions Introduction Introduction Cultivated Systems in 2000 cover 25% of Earth s terrestrial surface (Defined as areas where at least 30% of the landscape is in croplands, shifting cultivation, confined livestock production, or freshwater aquaculture) 5 6

2 Introduction Water resources 5-35% of irrigation withdrawals exceed supply rates and are therefore unsustainable (low to medium certainty) The case of water resources management 2008 European Summer School in Resource and Environmental Economics 7 The main challenges of WRM Definition of IWRM Securing water for people Securing water for food production Developing sustainable job creating activities Protecting vital ecosystems Dealing with variability Managing risks Raising awareness and understanding Forging the political will to act Ensuring collaboration across sectors and boundaries IWRM is a process which promotes the co-ordinated development and management of water, land and related resources, in order to maximize the resultant economic and social welfare in an equitable manner without compromising the sustainability of vital ecosystems. Not a single definition IWRM practices depend on context 9 GWP-TAC, GWP-TAC, 2000 Integration in IWRM Natural System Integration Integration is necessary but not sufficient, it cannot guarantee development of optimal strategies, nor the solution of conflicts; Two basic categories of within and between integration: Natural system: resource availability and quality Human system: resource use and depletion. Managing the continuum of water bodies (inland, coast, ocean); Managing water and land (river basin as a planning unit) Focus on Green water, not only on Blue water Managing surface and ground- waters Managing quantity and quality Managing up-stream and down-stream GWP-TAC, GWP-TAC,

3 Human System Integration Integration and Sustainability Mainstreaming and involving institutions, the private sector and stakeholders Implementing cross-sectoral approach and evaluation of impacts Considering macroeconomic effects of development Designing operational methods and tools for stakeholders involvement and conflict management and resolution Overriding criteria: Economic efficiency in water use (scarce resources water and finance) Equity (equal rights to access to water) Environmental and ecological sustainability (preservation of resources for future generations) 3 GWP-TAC, GWP-TAC, 2000 Sustainability Science and IWRM Core questions Focus on the dynamic interactions between nature and society, to learn how to:. integrate the effects of key processes across the full range of scales from local to global; 2. make society able to guide those interactions along sustainable trajectories 3. implement participatory procedures involving scientists, stakeholders, citizens, to transform knowledge claims into trustworthy, socially robust, usable knowledge, for the transition to sustainability. How to integrate nature-society interactions? 2. How evolving nature-society interactions will influence long term trends in environment and development? 3. What determines vulnerability and resilience of nature-society systems? 4. Can scientifically meaningful limits be defined? 5. What system (market, rules, ) can improve more the social capacity to guide interactions with nature? 6. How to improve systems for monitoring, modelling and reporting? 7. How can today s research activities be integrated into systems for adaptive management and societal learning? 5 JFK School of Government, Harvard Univ., JFK School of Government, Harvard Univ., 2000 Spatial decision and policy making 2008 European Summer School in Resource and Environmental Economics Decision making processes Building (and sharing) knowledge Analysis (observations, hypotheses, etc.) (mental, empirical, mechanistic, mathematical, etc.) Analysis 8 Courtney, 200 3

4 Effects of spatialisation methods 20 Raster data model Hydrologic fluxes (x,z) Spatial entities Discretization Sampling 2 Hydrologic fluxes (x,y) Hydrologic balance in agroecosystems (x,z) 4

5 Geostatistical spatial analysis Spatial filters ˆ γ ( h) = 2N( h) N ( h)[ ] 2 z( xi) z( xj) i j Criterion/factor maps Rainfall Land use Temperature Elevation Segmentation Hillshade Processes, patterns, systems Fractal Aspect C.dorsatus 27 Fuzzy membership to suitability for C.dorsatus Suitability analysis with MCE-OWA for C. dorsatus Avg. T Jul.0 Processes, patterns, systems Avg. T Jan Aspect Elevation Precip. Jul Slope Processes, patterns, systems

6 Suitability map Connectivity analysis Processes, patterns, systems TRUE POSITIVE (% Suitability C.dorsatus (Biomapper vs. MCE-OWA) Biomapper (ROC = 0.853) 0 Constrained MCE (ROC = 0.879) Processes, patterns, systems Green: suitable without populations 3 FALSE POSITIVE (%) 32 Identification of protected areas Socio-ecosystem: definition Processes, patterns, systems Socio-ecosystems Social-ecological systems (or socioecosystems; SES): complex adaptive systems where social and biophysical agents are interacting at multiple temporal and spatial scales; the concept emphasizes the adoption of a single integrated approach for the analysis of both social and economical agents and the natural components of the ecosystem Socio-ecosystem governance Pixelizing vs. socializing Socio-ecosystems The main challenge for the study of governance of social-ecological systems is improving our understanding of the conditions under which cooperative solutions are sustained, how social actors can make robust decisions in the face of uncertainty and how the topology of interactions between social and biophysical actors affect governance Build up adaptive capacity: the capacity of a SES to manage resilience in relation to alternate regimes Socializing the pixels: to take remote sensing and other geophysical data beyond their usual use in applied sciences, to address the concerns of social sciences (patterns processes) Pixelizing the social: linking socioeconomic infromation and models (e.g. S- ABM) with raster imagery (processes patterns)

7 Conceptual model 38 Relational diagrams and models LUC scenario models Once the relational diagram is finalised it can be used for building a mathematical model by implementing equations formalising the relations between external, state, auxiliary, and rate variables Cellular automata Distance from villages and loss of open areas loss of open areas (%) distance (m) NO3_OUT Nitrate transport in surface waters ORGN_OUT Impact indicators YLD Crop production Decision making process Organic nitrogen transport in surface waters 4 7

8 Decision making process Knowledge based DM process Problem recognition Analysis Decision making processes Decision making processes Public participation Simulation Choice / Decision Implementation Problem definition Alternative generation Scenario analysis 43 Courtney, Decision making processes DM is and iterative process Scenarios and simulations 45 Adapt. from Belton and Steward, 2002 Need for scenario analysis Scenarios Scenario analysis and simulation Finding #3 of MEA: The degradation of ecosystem services could grow significantly worse during the first half of this century and is a barrier to achieving the Millennium Development Goals Scenario analysis and simulation Scenario: A plausible and often simplified description of how the future may develop, based on a coherent and internally consistent set of assumptions about key driving forces and relationships. neither predictions nor projections narrative storyline. derived from projections of models but often also from additional information from other sources. A small set (typically 3 or 4) of scenarios is usually created and analyzed for investigations into possible/plausible futures

9 IPCC SRES Scenarios Potentials of scenario approach Scenario analysis and simulation Scenario analysis and simulation Scenarios can help evaluate different action steps and identify "robust" actions (decisions/policies) that make sense across a wide variety of future conditions. Scenarios development is a fundamental component of decision making Scenarios are especially important where there is high uncertainty about the future. A set of several significantly different scenarios helps "bound the uncertainty" of the future so that an organisation can systematically plan for future contingencies and clarify its preferred vision of the future. 49 IPCC SRES 50 Institute for Alternative Futures Scenario analysis and simulation Suitability: current vs. HadA-2020 Current suitability HadA suitability 5 Change detection The DPSIR meta-model and communication framework Driving forces = Underlying causes and origins of pressure on the environment Pressures = The variables which directly cause environmental problems State = The current condition of the environment Impact = The ultimate effects of changes of state, damage caused Response Response = Decisional option = Effort to solve the problem caused by the specific impact Driving Forces Pressures State Impact Integrated Assessment Integrated Assessment: a process of combining, interpreting, and communicating knowledge from diverse scientific disciplines in such a way that the whole set of cause-effect interactions of a problem can be evaluated from a synoptic perspective with two characteristics:. It should have added value comparable to single disciplinary oriented assessments 2. It should provide useful information to decision makers (Rothmans and van Asselt, 996) Integrated Assessment : computer based processes and tools to analyse and simulate the spatio-temporal behaviour of complex systems in relation to human planning and decision making

10 Integrated Integrated and EIA in the DPSIR framework Effects of External Drivers Problem solving approach DPSIR framework as an IA [meta]model IAM in the DPSir framework

11 : 2: 3: 4: : 2: 3: 4: : 2: 3: 4: : : : : FORZANTI ESTERNE 2: DETERMINANTI 3: PRESSIONI 4: STOCK RISORSA,40,25 0,3,05,05 0,95 0,0,00 0,70 0,65 0,07 0, Time 0.33 mer 8 mag 200 : PROGRAMMA MISURE Untitled Time 0.33 mer 8 mag 200 Untitled IAM in the DPSir framework IAM in the DPSIR framework 6 62 A schematic DPSIR model for water resources management Planning and Decision Making in the DPSIR framework SISTEMA TERRITORIALE: RISORSE IDRICHE FORZANTI ESTERNE RISPOSTA ~ S DPS DETERMINANTI STATO RISORSA PRESSIONI IMPATTO STOCK RISORSA Rinnovazione PROGRAMMA MISURE LIMITE IMPATT ACCETTABILE MISURA Tasso rinnovazione IR Planning and Decision Making in the DPSIR framework MCA in the DPSIR framework 65 66

12 MCA in the DPSIR framework Spatial information in the DPSIR framework Spatial multi-criteria analysis Spatial multi-criteria evaluation RD R MT R NT ER /4 /4 /4 /4 Distance to water Landscape diversity 3/4 /4 RD L r MT L /2 /2 Protection of groundwater Vulnerability of ground water Scenario : Impacts on groundwater Scenario 2: Impacts on groundwater Impact index for surface water Vulnerability of surface water Impact index for groundwater Vulnerability of groundwater /2 /2 /2 /2 Scenario Scenario 2 RISK FOR SURFACE WATER RISK FOR GROUNDWATER Scenario : Risk for groundwater Scenario 2: Risk for groundwater Difference map EVALUATION OF ALTERNATIVE LAND USE SCENARIOS 70 Concluding remarks 2008 European Summer School in Resource and Environmental Economics Concluding remarks Methodological remarks Spatial data analysis may represent a significant part of the theoretical background of ecological and economic analyses (assumptions, robustness, etc.); Analysing socio-ecosystems without robust spatial methods is like analysing time series without knowing the chronological order of data; Integrated models could contribute to improving decision/policy making processes; DSS s based upon the DPSIR framework, in combination with GIS, IAM and MCA functionalities show great potential for NRM; Significant gaps do exist between scientific knowledge and policy making. 72 2

13 Filling the science-policy gap (/2) Filling the science-policy gap (2/2) Concluding remarks Different priorities and objectives of stakeholders and researchers are the main causes of the existing gaps Key actors should be preliminary identified and involved all phases of the decision making process It is necessary to adapt approaches and tools to the users needs and not vice-versa Flexibility should be assured all along the development and implementation process Supporting the decision process also means making knowledge accessible and easy to understand The ability to implement expert knowledge (i.e. detained by qualified persons) in the process is of fundamental importance Concluding remarks Indicators play a fundamental role in providing concise and targeted quantitative features of the various aspects to be considered in the choice A plethora of approaches is available for the assessment of alternative options Sensitivity and uncertainty analysis, and quality assurance should be carried out during all the development phases and the outputs associated with the results Capacity building and training of end-users (policy makers or consultants) are necessary to ensure that the process is not mismanaged or the tools misused The improvement of the quality of the decision process is the main indicator of success