World Resources Insitute activities

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World Resources Insitute activities

WRI’s CAIT Database

of Emissions from

LULUCF &

Climate Applications

for the World Intact

Forest Landscapes

Susan Minnemeyer

World Resources Institute


Overview

• WRI’s Climate Analysis Indicators & Tools

(CAIT) update on GHG emissions from

LULUCF

• Intact forest landscapes – co-benefits for

biodiversity and other ecosystem services


CAIT: Linking Data and Decision-making

Free, online at http://cait.wri.org


CAIT Data Uses

• Media

• Communication to

decision makers

• Education

• Policy advocacy


LUCF Share of Global Emissions


Emissions from Land Use Change

– from top emitting countries

800,000

700,000

600,000

500,000

400,000

300,000

200,000

100,000

0

Indonesia

Brazil

Malaysia

Myanmar

Congo, Dem. Republic

Zambia

Nigeria

Peru

Papua New Guinea

Venezuela

Nepal

Colombia

Tons of Carbon


Comparison of Land Use Change

data sources


Shortcomings of current database

• Outdated (2000)

• Only partially based on

spatial or remotely

sensed data

• Extensive assumptions

• High uncertainty


Tier level of assessment

Approach for activity data: Area

change

1. Non-spatial country statistics (e.g. FAO)

—generally gives net change in forest area

Tiers for emission factors:

change in C stocks

1. IPCC default values

2. Based on maps, surveys, and other

national statistical data

3.Spatially specific data

•From interpretation of remote sensing data

•National inventory of permanent plots with

repeated measurements

2. Country specific data for key

factors

3.National inventory of key

carbon stocks, repeated

measurements of key stocks

through time


Updating & Improving CAIT

Study goals:

• Engage experts to identify best available & new

information

• Develop improved methods for estimating GHG

emissions from LULUCF

– Recent, comparable data; consistent method

• Produce new global estimates in a timely manner

– Provide an independent check and balance for decision-makers


New data availability

Factor

Area of forest loss

(clearing of forest

for other land use)

Original data source

used for CAIT

FAO Forest Resources

Assessment 2000

Current available datasets

• FAO Forest Resources Assessment 2005

• MODIS/Landsat Tree Cover change

(Hansen et al. 2008) (Tropics, boreal)

• TREES-3 (JRC)

• Regional and national assessments

(various)

Forest biomass

FAO Forest Resources

Assessment 2000

Timber removals FAOSTAT FAOSTAT

• FAO Forest Resources Assessment 2005

• IPCC Good Practice Guidance for LULUCF

• Improved land cover datasets (e.g.,

GLOBCOVER)

• National assessments

Fires Not considered • FIRMS, MODIS burned area mapping,

Globcarbon, World Fire Atlas, etc.

Afforestation FAO FRA Spatial data

Emission factors

IPCC default values from

broad forest categories

Various regional and local studies


Forest cover loss: Boreal vs. Tropics

Boreal

Humid Tropics

Biome area, million ha 2,150.9 1,962.4

Forest area 2000, million ha 872.3 925.1

% forest loss 2000-2005 (standard error) 1.63 (0.10) 1.39 (0.08)

Area of forest loss 2000-2005, million ha 35.1 27.2

% Forest loss area of forest 2000 area

Source: Hansen, Potapov et al., SDSU

4.0

2.25 excluding fire

2.4


Intact Forest Landscapes


World Intact Forest Landscapes

Greenpeace Russia

WRI GFW Network

University of Maryland

Available online at www.intactforests.org


Logging monitoring


Logging monitoring

Forest Forest cover cover loss loss hotspot hotspot percent:

Outside IFL IFL 0.5 0.5

Within Within 5-km 5-km IFL IFL periphery zone zone 0.8 0.8

Within Within IFL IFL core core area area 0.2 0.2

Forest cover loss hotspots within intact forest landscapes

2001 2002 2003 2004 2005

A

B


Wildlife Conservation Society Announces

Estimated 125,000 Western Lowland Gorillas

Remain in intact Central African forests

New York Times, Aug. 4, 2008


Thank you

Susan Minnemeyer

Senior Associate/GIS Manager

People and Ecosystems Program

World Resources Institute

202-729-7795

susanm@wri.org

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