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Early Warning System: monitoring aspect

Early Warning System: monitoring aspect. Celso von Randow Earth System Science Center - INPE. celso.vonrandow@inpe.br. EWS framework. Remote sensing monitoring system. Modeling System. In situ monitoring stations. Monitoring system Modeling System Analysis Tools

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Early Warning System: monitoring aspect

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  1. EarlyWarning System: monitoringaspect Celso von Randow Earth System Science Center - INPE celso.vonrandow@inpe.br

  2. EWS framework Remote sensing monitoring system Modeling System In situ monitoring stations • Monitoring system • Modeling System • Analysis Tools • Communications division EARLY WARNING SYSTEM

  3. Early Warning System • Which ecosystem services and other properties of the Amazon would be important to monitor and prevent from tipping into a degraded state ? • What to warn about? • Degradation of ecosystem services in what time scales (years – decades) ? • Not only critical transitions, but also gradual change

  4. Critical indicators • The basis of such a system is long-term monitoring of critical indicators • These indicators should be quantities that are relatively accessible, and easy to monitor at high temporal and/or spatial resolution. • should represent the variability of the Amazon ecosystem services and other important tipping phenomena => their behaviour near critical transitions should reliably point to imminent change in the state of that particular ecosystem service.

  5. Tipping point early warning signals System being forced past a bifurcation point yt+1 = ayt + sht a= exp(- kDt) k→0 and a→1 at bifurcation

  6. Alternative stable states? FrequencyofTree Cover (Global) Forest state: T ≥ 60% Treelessstate: T <5% Savannastate: 5% ≤ T < 60% Hirota et al., Science, 2011

  7. Tree cover X MAP (global): Schefferet al., TREE, 2003 Hirotaet al., Science, 2011

  8. Tree cover X MAP (global): Statistical procedure (Livinaet al., 2010) confirmed 3 classes: Schefferet al., TREE, 2003 Hirotaet al., Science, 2011

  9. Analysis tools • Generic Early Warning indicators – detection on basis of change in variability

  10. Analysis tools • Generic Early Warning indicators – detection on basis of change in variability • Detection on basis of exceedance of critical thresholds - analysis of trends and changing trends

  11. Analysis tools • Generic Early Warning indicators – detection on basis of change in variability • Detection on basis of exceedance of critical thresholds - analysis of trends and changing trends • Identification of outliers from analysis of PDFs – (given a range of conditions that sustain a particular forest, look into predictions of extremes)

  12. List of possible variables to monitor • Sea Surface Temperature (SST) - indicator of global-scale change • Precipitation (patterns, quantity, dry season length…) primary driver as well as an ecosystem service that can be affected • Climate modes (ENSO, Atlantic Oscillations, etc) - often correlated indicators of high-impact changes or episodes in Amazonia • River flow and discharge • Evapotranspiration - prime driver of recycling

  13. List of possible variables to monitor • overall vegetation productivity changes – [CO2] over the tropical belt + anthropogenic emissions • Biomass - remote sensing (eg S-band Radar) and well-referenced growth bands in forest plots across the basin • Water use efficiency from tree-ring & gas exchange monitoring • Remote sensing indices (NDVI , EVI)

  14. List of possible variables to monitor • Fires (remote sensing and in-situ observations) – not simply occurrence or area, but also fire effects (e.g. type of vegetation affected and recovery of previously burned areas • Economic indicators, such as the GDP of the region, transport, trade and migration patterns • Exposure and Vulnerability (?)

  15. COSMOS (COsmic-ray Soil Moisture Observing System) Could it be used to monitor ‘flammability’ of the forest? Monte-Carlo Simulation of Neutron Density This is largely a soil-dependent “shift”, SO ONLY ONE FIELD CALIBRATE NEEDED In drier soil, more neutrons escape Monte-Carlo Simulation of Neutron Density COSMOS probes detect neutrons at two energies, but use “fast” neutrons for soil moisture detection because calibration is less sensitive to the chemistry of the soil (thermal neutrons give information on above-ground water, e.g. snow cover) Fast Neutron Detector In moister soil, less neutrons escape Thermal Neutron Detector

  16. COSMOS (COsmic-ray Soil Moisture Observing System) Example COSMOS Data for the San Pedro Basin Gravimetric samples are in red, with sampling error Soil moisture from cosmic-ray neutron data compared with gravimetric samples How many point measurements are needed to get a similar (2%) precision in area-average soil moisture? For the (single) calibration of a COSMOS probe (made at installation), soil will be sampled at 3 depths, 8 directions, and 3 radii around the probe (i.e., 72 samples). Diurnal Cycles (moisture redistribution)

  17. Institutional and practical embedding • From stakeholders consultation: • EWS: MMA, MAPA, MME, MDA • ‘Users’ / Policy makers: MMA, SAE (Secret. AssuntosEstratégicos),CENSIPAM (Centro Gestor e Operacional do Sistema de Proteção da Amazônia), Órgãos Estaduais de Meio Ambiente (OEMAs)

  18. Communication • Communication of complex issues to non-science audience is a major challenge • Design should be (as much as possible) stakeholder-driven (e.g. focus on critical transitions in environmental conditions or direct impacts in ecosystem services) ? • Reduce risk of false positives

  19. Conclusions Design of an Early Warning System for critical transitions in the Amazon region: • Requires a multi-disciplinary approach and involvement of relevant stakeholders • Based on long-term monitoring of critical indicators that should be relatively accessible to monitor and should represent the variability of relevant ecosystem services • Their behaviour near critical transitions should reliably point to imminent change in the state of that particular service. • Through model analysis and analysing data sets, the most efficient monitoring and analysis tools need to be designed • Communication is a major challenge for effective policy actions

  20. WP2 runs (Moore protocol) Simulation A (Potential vegetation A): natural disturbances + no land-use change + changing climate (recycling the SHEF driver) + changing CO2. Simulation B (Potential vegetation B): natural disturbances by excluding fire + no land-use change + changing climate (recycling the SHEF driver) + changing CO2. Simulation C ( Changing climate ): This simulation need to be achieved by two steps: 1) natural disturbances + no land-use change + changing climate (recycling the SHEF driver) + changing CO2 from 1715 to 1970; 2) natural disturbances + no land-use change + changing climate + constant CO2 (=325.713 ppm) from 1970 to 2008. Simulation D (Full changes): natural disturbances + land-use change + changing climate + changing CO2.

  21. WP3 runs

  22. How to achieve a sustainable future? “Well managed natural resources, ecosystem services provision and low greenhouse emissions” High Environmental Development Environmental Economic Social A High Social Development “In 2050, Brazil is one of the main economies of the world. Social indicators also place Brazil among the most equitable and socially fair countries in the world. Society as a whole has access to high quality education, health services, economic opportunities, supported by strong institutions.” Economic Environmental Low Social Development “In 2050, Brazil is one of the main economies of the world, but structural inequalities in society persist. Land in rural areas is highly concentrated, urban areas remain violent, segregated, with bad quality services in poor neighborhoods.” Vision A: High, High Sustainable Vision B Low,High Vision D Low, Low Vision C Low, High Low Environmental Development “Badly managed natural resources, few natural vegetation areas remaining, and high greenhouse emissions.” Social Economic Economic NationalStorylines (basedon Nobre et al., forthcoming)

  23. LUCC spatially explicit models adapted from Verburg et al., 2006

  24. LuccME / BrAmazonia model summary

  25. Selection of relevant policies

  26. Policies International and national non-Amazonian: • UNFCCC: Decisions taken during COP 17 change the accounting rules applying to the land-use sector and to wood converted to products. These new rules are, however, unlikely to increase pressure to import wood from non-EU nations to an important extent. • Nationally appropriate mitigation actions (NAMAs). These are voluntary actions by development countries and countries in transition to reduce GHG emissions, aiming at seeking and matching international financial, technology, and capacity-building support for proposed actions and at recognizing individual actions which may be implemented without international support. NAMA registry is not yet operational and given the vague definition and the wide range of support options, they can be expected to strongly overlap or to be combined with instruments such as credit generation for the carbon markets. • Reducing emissions from deforestation and forest degradation (REDD) - Multilateral initiatives: UN-REDD programme, Forest Carbon Partnership Facility (FCPF), Forest Investment Program (FIP), and REDD+ partnership; bilateral agreements; and the voluntary carbon market. • Standards and certification

  27. Policies Brazilian Forest Code (recent modifications, debate ongoing) Action Plan for Prevention and Control of the Legal Amazon Deforestation (PPCDAM) (significantly reduced deforestation rates since 1994) Credit and subsidies program – National Environment Program, Green Aid, Protected Areas Fund, Climate Fund, and agricultural policies. Soy moratorium Land titling Land zoning Food purchase program Payment for environmental services Infrastructure for transportation and energy Climate change plans, including REDD+ in each Amazonian state

  28. Policies The Brazilian Forest Code: rationale and current status - Created almost 50 years ago, intended to be a tool for soil/water resources management and for environment protection. In 1996, the government decided to increase the protected area to 80% of any property in the Amazon. However, compliance to the Forest Code was not always observed, with implications to forest conservation and agriculture expansion. In an attempt to minimize the problem, the Congress recently approved many modifications on the Forest Code. To date, the debate has continued. Credit and subsidies program - This includes a National Environment Program, Green Aid, Protected Areas Fund, a Climate Fund, and agricultural policies. Soy moratorium - Anticipating the possibility that trade barriers could be built against Brazilian exports, ABIOVE (Brazilian Vegetable Oil Industry Association) and ANEC (Brazilian Grain Exporters Association) decided not to purchase this grain originated from areas of the Amazon Biome deforested after July 2006. Land titling - In 2009, the government initiated program with the main objective to promote legal land use by legitimating previous occupations. Land zoning Food purchase program Payment for environmental services Infrastructure for transportation and energy - Several main roads traversing the Amazon are in the process of being paved and increasing accessibility. Climate change plans, including REDD+ in each Amazonian state Program for the Acceleration of Development PAC Action Plan for Prevention and Control of the Legal Amazon Deforestation (PPCDAM) - PPCDAM is an attempt of Brazil to reduce deforestation of the Brazilian Amazon Forest. Implemented in 2004, it significantly contributed to the decrease of deforestation rates, discouraging illegal deforestation in Amazon Forest.

  29. SummaryofLuccME/BRAmazoniaScenarios – v1 – March, 2013

  30. Deforestation rates C and D: Mirroring past curve B: Voluntary targets until 2020 A: Zero deforestation after 2020

  31. Quantifiable phenomena that affect ecosystem services • Precipitation - crucial to maintain both natural vegetation and agriculture, replenish rivers and maintain evapotranspiration • Recycling of moisture and evapotranspiration (moisture transport) • River discharge – navigability/communications and habitability of river margin people communities in the region, as well as fisheries and the vitality of floodplain ecosystems (varzeas) • Biomass and productivity of vegetation (forests) - carbon stored and sequestered by the region; large economic value in terms of timber.

  32. Quantifiable phenomena that affect ecosystem services • Agricultural productivity - mainly grass for cattle, soy beans, a range of newly developed, sustainably produced cash crops (Açai, Guarana, etc), palm oil and various regional products • People migration and economy. Migration can enhance deforestation but also be a consequence of a degrading environment • Land-use change itself affects most of the variables, as well as being associated with fire and air quality (smoke and nitrogen emissions).

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