linking policies through land use scenarios to ecosystem services loss

Linking policies through land use scenarios to ecosystem services loss

Ana Paula Dutra de AguiarEloi Lennon Dalla Nora

São José dos Campos, April of 2014

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Topics

Introduction: Modeling approaches International x regional factors

Results Eloi’s BRAmazon+BRCerrado results (Scenarios GAM, RAM,

GAM+BT, RAM+BT) AMAZALERT BRAmazon results – Scenario A, B and C

(2100)

Introduction

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General structure of LUC models

Despite the diversity of land use models found in the literature it is possible to identify a common functional structure that is valid for most of the available cases;

Dalla-Nora et al., (no prelo)

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LUC MODELS FOR THE AMAZON

Laurance et al., 2001

2020 2020 2050

2030 2050

Aguiar et al., 2006 Lapola et al., 2011

Nepstad et al., 2008 Soares-Filho et al., 2006

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Quantity of change in LUC models

None of the previous studies were able to plausibly capture the general trajectory of land cover change observed in this region during the last decade;


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Quantity of change in LUC models

Modeling approaches:

Global approach

Intra-regional approach


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Model results and Amazon LUC dynamics

Models structure requires a clear differentiation between the spatial and underlying drivers of change;

Laurance e al., 2001 Laurance e al., 2001

Machado, 2002

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If Amazon deforestation was a result of price movements, we would expect that the slowdown in deforestation would be conjunctural and temporary;


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Protected areas (PAs) 240 new PAs from 2004 +65% over 2000-2004 55% of the remaining forests.

Credit access All lines of rural credit -65% (all rural municipalities) -77% (MT, PA, RO)

Command and control Monitoring and enforcement +8.823 fines 70 times more over 2000-2004


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Previous modeling studies were not able to integrate the global and regional forces that shape land use dynamics in the Amazon;

Scenarios' formulation was also quite simplistic which compromised their ability to explore contrasting pathways;

It's necessary to adopt an innovative modeling framework to represent land use systems as open systems;

Modeling results combining MAGNET and LuccME

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Eloi Dalla Nora’s thesis

Dalla-Nora et al., (submitted)

The central idea is to represent land systems as open systems; Global scale Regional scale Direct LUC drivers Underlying LUC drivers Intra-regional dynamics

Lucc-ME

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Land demand


National land demand is split over AEZs, as defined in the GTAP-8 LUC-Database, the GeoDB consistent with the Economic GTAP-8 DB used in MAGNET;

Spatial distribution of the global AEZs and Brazil’s biome-driven AEZs aggregation

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Land allocation

Aguiar et al., (2012)

Land demand projections are allocated based on spatially explicit LUC models built on top of the LuccME Framework;

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Scenarios

A global baseline scenario (based on USDA (2012) and IPCC (2013) GDP and population projections) was run testing different regimes of land use regulation up to 2050;

Population Growth

World Brazil

33% 19%

GDP GrowthWorld Brazil

183% 185%

Production Growth

World Brazil

109% 110%


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Land demand

Such strategy allowed to simulate key land use policies for the Amazon;


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Scenarios


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ACCESSIBILITY – SCENARIO RAM (AMAZALERT C

2030202520152010

2010 2050

2042

Paved Roads - Log10(Minimum distance to the nearest Federal or State road)

Unpaved Roads - Log10(Minimum distance to the nearest unpaved Federal or State road)

Connection to National Markets (index representing the degree of connectivity to SP and NE through the roads network)

Very close Very distant

Low High

Very close Very distant

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2022202020182010

2010

PROTECTED AREAS - SCENARIOS A and B2010 2050

PROTECTED AREAS - SCENARIO C2010 2050

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Land allocation

Land demand projections could also lead to contrasting land cover change patters;

RAM GAM

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Land allocation

Biofuel targets could strength the deforestation patters observed under the GAM and RAM scenarios;

RAM+BT GAM+BT

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Some results for the AMAZON

AMAZALERT RESULTS

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Amount of change

LUCCME Demand (scenarios)

MAGNET global model

Stakeholder inputs

Spatial Patterns

LUCCME Potential/Allocation

(scenarios)

Visions – Stakeholder inputs

Biophisical, socioeconomic and institutional factors affect the Demand and Allocation

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Amount of change

LUCCME Demand (scenarios)

MAGNET global model

Stakeholder

Spatial Patterns

LUCCME Potential/Allocation

(scenarios)

Visions – Stakeholder inputs

Biophisical, socioeconomic and institutional factors affect the Demand and Allocation

Global: population, GDP and production growth + biofuels targets Regional: roads, protected areas, credit

Regional: roads, protected areas, law enforcement

Storylines and contrasting rates of change

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IV - Contexto institucional

Futuro e Trajetória em torno de quatro temas:

I - Recursos naturais

II - Desenvolvimento social

III - Atividades econômicas

Presente

DESENVO

LVIMEN

TO

SOCIO

ECON

OM

ICO

DESENVOLVIMENTO AMBIENTAL

ALTO

ALTOBAIXO

BAIXO

CENÁRIO A:SUSTENTABILIDADE

CENÁRIO B:MEIO DO CAMINHO

CENÁRIO C:FRAGMENTAÇÃO E CAOS

AMAZALERT1ª e 2a OFICINA de STAKEHOLDERS

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STAKEHOLDER WORKSHOPS IN BRAZIL

IV - Contexto institucional

Presente, Futuro e Trajetória em torno de quatro temas:

I - Recursos naturais

II - Desenvolvimento social

III - Atividades econômicas

ETAPA 1: organizações da sociedade civil e setor produtivo

ETAPA 2: organizações da sociedade civil, setor produtivo, governo e pesquisadores

ETAPA 1 (Belém):

primeira definição dos cenários

ETAPA 2 (Brasília):

refinamento das trajetórias

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International policies (WP4 report)International policies and initiatives

UNFCCC forest management and harvested wood products accounting Nationally appropriate mitigation actions (NAMAs) Reducing emissions from deforestation and forest degradation (REDD) REDD under the voluntary carbon market Standards and certification National and regional policies and initiatives outside of Amazonian nations EU renewable energy directive (EU RED)

Mandatory national renewable energy targets Sustainability criteria for biofuels Sustainability Criteria for biomass for heat and power

U.S. programs U.S. Renewable Fuel Standard 2 (RFS2) U.S. Stationary sources, proposed approach California Low Carbon Fuel Standard

Chinese policies and trade Biofuel targets in China The current and future soybean trade between China and Brazil

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Brazilian public policies affecting the Amazon (WP4 report)

FOREST CODECREDIT AND SUBSIDIES PROGRAMS SOY MORATORIUM POLICY FOR 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 Program for the Acceleration of Development PAC Action Plan for Prevention and Control of the Legal Amazon Deforestation (PPCDAM)

AMAZALERT Scenario A, B and C (2100)

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Some results for the AMAZON

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Prepared by Eloi Dalla Nora

For comparison RCP (~10 000km2)

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Premises

Scenario C19500 km2yr-1 (until 2100)(ave 1996-2005)

Scenario B:3900 km2 in 2020(20% 19500 km2)

Scenario A:“Zero”Deforestation

Scenario D? 10000km2

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(A) Scenario A: Deforestation in 2050 (B) Scenario B: Deforestation in 2050 (C) Scenario C: Deforestation in 2050

(D) Scenario A: Secondary Vegetation in 2050

(G) Scenario A: Agriculture in 2050 (H) Scenario B: Agriculture in 2050 (I) Scenario C: Agriculture in 2050

(E) Scenario B: Secondary Vegetation in 2050 (F) Scenario C: Secondary Vegetation in 2050

Scenario C v28 – May 2014

BRAmazon, BRBolivia andROBIN

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(old growth or primary) Forest cover – 2100

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2100(old growth or primary) Forest cover - 2050

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(old growth or primary) Forest cover - 2075

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(old growth or primary) Forest cover - 2100

Brazilian Amazon: 60% deforested(fragemented in most cells, 20% remaining)

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Summary

We can create storylines for Scenario C (RAM /RAM –GT) and Scenario A (GAM) Usining the stakeholder meetings mentioning the policies W4 reported

Resulting in the spatial scenarios Ecosystem Services: derived indicators

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Example: Derived indicator related to CO2 emissions

linking policies through land use scenarios to ecosystem services loss

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