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MNV/RL 1 Developing historic land cover databases The BIOME 300-experience Prof. Dr. Rik Leemans [[email protected]] Dutch Institute of Public Health and the Environment

MNV/RL 1 Developing historic land cover databases The BIOME 300-experience Prof. Dr. Rik Leemans [ [email protected]] Dutch Institute of Public Health

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MNV/RL 1

Developing historic land cover databases

The BIOME 300-experience

Prof. Dr. Rik Leemans[[email protected]]

Dutch Institute of Public Health and the Environment

Land and land use

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The traditional use of land in most global carbon-cycle models

• Often initialized by modeled potential vegetation, not actual vegetation

• tropical deforestation is the only land-use change considered

• Land conversions included but generally no land modifications

• Still a missing sink (i.e. the different approaches do not agree on the current global budget)

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Improving the carbon cycle • Inter-annual variability is added to the models: the

biosphere reacts rapidly

• Include realistic patterns of deforestation and reforestation

• Add realistic management for forests, pastures and agriculture

• Develop a good high-resolution initialization database for the recent past: BIOME 300

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Using the current understanding for

explaining past and projecting future

climate

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Why historic land-cover databases?

•Testing against historical data is an important step for validating integrated environmental models of global change

•The description of historic carbon budgets and land-climate interactions require good initialisation data

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An example: HYDE (hundred year database on the environment)

• Basic Driving Forces

• Energy & Industry data

• Terrestrial data

• Oceanic & Atmospheric data

• Population, GDP, value added, private consumption,

climate data

• Energy consumption, GHG emissions, industrial production

• Land use, crop production (area and yield), animal production, food and fertilizer consumption livestock numbers, etc.

• Concentration of GHGs

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World Population Prospects 1950 - 2050, United Nations Population Division, the 1996 Revision.

International Historical Statistics, B.R. Mitchell (1975 - 1995)

&

Country Census data

&

Logistic curves for countries with ‘no data’ or ‘filling the gaps’

1994

1950

e.g.1800

The total population numbers per country are scaled down by a factor derived from the historical statistics, and then allocated according the 1994 NCGIA population density map.

0.5 degree lat/lon population density map, NCGIA (1995)

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Excel spreadsheets arable area, pasture Export to csv format

The total land use estimates per country are derived from historical statistics, and then allocated according to HYDE 2.0 population density maps (proxy for arable area)

and a methane emission density map (proxy for pasture)

country1 country 204year 1700 .…. ..… ….. …... .…. ..… ….. …... .…. ..… ….. …... .…. ..… ….. …...year 1995 .…. ..… ….. …...

Fortran routines, allocating areas to IMAGE grid cells

Export to ascii matrix, and import in Arc/Info as grid

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Arable land and pastures in HYDE

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Arable land and pastures in HYDE

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Disadvantages of the global backcasting approaches

• Coarse scale patterns are captured but locally many discrepancies remain

• Non-linearities neglected through the scaling

Major challenges:

How to improve the regional historic land use and land-cover patterns?

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Regional historic reconstructions

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Land used in Harvard Forest

The mixed natural forest before the settlement of Europeans in 1700

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Landuse in Harvard Forest

Deforestation of small farms by earlier settlers in 1740

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Land use in Harvard Forest

Maximum of agraricultural land use in 1830

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Land use in Harvard Forest

Most farms abandonned in 1850. The new forests are composed of pine

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Land use in Harvard Forest

Pine forests for wood production on abandonned land in 1910

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Land use in Harvard Forest

Natural regeneration of mixed broadleafed forests replace the cut pine forests in 1930

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Land use in Harvard Forest

The currentsituation of Harvard Forest, one of the most researched, relatively young broadleafed forests

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Remote sensing approaches

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Deforestation in Rondônia in 1970

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Deforestation in Rondônia in 1973

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Ontbossing in Rondônia in 1976

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Deforestation in Rondônia in 1978

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Deforestation in Rondônia in 1985

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Deforestation in Rondônia in 1988

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Deforestation in Rondônia in 1991

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Deforestation in Rondônia in 1996

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Emperical models of the dynamics of deforestation

Period 1986 to 1987

Closed bos

Agriculture

Regowth forests

deforested again 1973 ha/year

abandonned: 2902 ha/year

Degradation: 1543 ha/year

deforestation: 4112 ha/year

Period 1988 to 1989

Closed forests

Agriculture

Regrowth forest

deforested again 6210 ha/year

abandonment: 7203 ha/year

degradation 5294 ha/year

deforestation 8634 ha/year

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Farms along the TransAmazon Highway in Altamira, Brazil

Deforestation

Different drivers in different regions: include the humans dimenison

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An example of extreme events

woodlandGrasslands

Arable land

An extreme rain eventSource: Bork et al., 1998

Soil erosion

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Conclusions• Natural and socio-economic extreme events are

important in defining historical trends

• Top-down and bottom-up approaches must be linked to improve the resolution of the global data

• The scientific communities on past (PAGES), present (LUCC, BAHC & GCTE) must work together with help of historians

• The PAGES HITE initiative is a good start to continue with a BIOME 300 activity