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© ICFR 2014 Modeling risk on planted forests in South Africa Ilaria Germishuizen Institute for Commercial Forestry Research (ICFR) Pietermaritzburg (South Africa) [email protected]

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Page 1: Modeling risk on planted forests in South Africa · 2018-01-11 · Risk modeling • Climate change - Shifts in optimal forestry areas - Drought risk - Fire risk - Frost risk - Site

© ICFR 2014

Modeling risk on planted forests in South Africa

Ilaria Germishuizen

Institute for Commercial Forestry Research (ICFR) Pietermaritzburg (South Africa)

[email protected]

Page 2: Modeling risk on planted forests in South Africa · 2018-01-11 · Risk modeling • Climate change - Shifts in optimal forestry areas - Drought risk - Fire risk - Frost risk - Site

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Monitoring and Assessment of Drylands: Forests, Rangelands, Trees, and Agrosilvopastoral Systems. FAO Headquarters, Rome, Italy, 19-21 January 2015

© ICFR 2015

Background: Forestry in South Africa • Static land base of 1 300 000 ha (1% of the country).

• Plantations of exotic tree species (Genera: Pinus, 52%; Eucalyptus, 40%; Acacia, 7%; Other, 1%).

• Single species – even age units/compartments.

• Short rotation (pulp: 6 – 14 years; sawtimber: 25 – 30 years).

Summer rainfall region

Winter rainfall region All year rain

Page 3: Modeling risk on planted forests in South Africa · 2018-01-11 · Risk modeling • Climate change - Shifts in optimal forestry areas - Drought risk - Fire risk - Frost risk - Site

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Monitoring and Assessment of Drylands: Forests, Rangelands, Trees, and Agrosilvopastoral Systems. FAO Headquarters, Rome, Italy, 19-21 January 2015

© ICFR 2015

Research focus Risk modeling • Climate change - Shifts in optimal forestry areas - Drought risk - Fire risk - Frost risk - Site x genotype matching breeding strategy - Adapting silvicultural practices to reduce risk and enhance productivity • Pests and pathogens - Bioclimatic risk models - Sensitivity studies

} New and existing P&D

Page 4: Modeling risk on planted forests in South Africa · 2018-01-11 · Risk modeling • Climate change - Shifts in optimal forestry areas - Drought risk - Fire risk - Frost risk - Site

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Monitoring and Assessment of Drylands: Forests, Rangelands, Trees, and Agrosilvopastoral Systems. FAO Headquarters, Rome, Italy, 19-21 January 2015

© ICFR 2015

Model Name Institution Country Mk3.5, 2001 Centre for Australian Weather and Climate Research (CAWCR) Australia

GFDL-CM2.0, 2005 National Oceanic and Atmospheric Administration (NOAA) Unites States GFDL-CM2.1, 2005 National Oceanic and Atmospheric Administration (NOAA) Unites States

MIROC 3.2, 2004 Centre for Climate System Research (CCSR), University of Tokyo Japan

ECHAM 5, MPI-OM, 2005 Marx Plank Institute for Meteorology Germany UKMO-HadGEM1, 2004 Hadley Centre for Climate Prediction and Research, Met Office United Kingdom

• Six Global Circulation Models (GCM) • Regionally downscaled • SRES: A2 • Monthly precipitation, tmax, tmin from 1960 to 2100

Main trends for Southern Africa: • MAT increases up to twice global rate • MAP: Some areas becoming dryer, other wetter. Erratic rainfall patterns. • Increase in frequency and intensity of extreme events (drought, extreme temperatures, extreme rainfall events)

Climate change

Page 5: Modeling risk on planted forests in South Africa · 2018-01-11 · Risk modeling • Climate change - Shifts in optimal forestry areas - Drought risk - Fire risk - Frost risk - Site

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Monitoring and Assessment of Drylands: Forests, Rangelands, Trees, and Agrosilvopastoral Systems. FAO Headquarters, Rome, Italy, 19-21 January 2015

© ICFR 2015

Page 6: Modeling risk on planted forests in South Africa · 2018-01-11 · Risk modeling • Climate change - Shifts in optimal forestry areas - Drought risk - Fire risk - Frost risk - Site

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Monitoring and Assessment of Drylands: Forests, Rangelands, Trees, and Agrosilvopastoral Systems. FAO Headquarters, Rome, Italy, 19-21 January 2015

© ICFR 2015

Page 7: Modeling risk on planted forests in South Africa · 2018-01-11 · Risk modeling • Climate change - Shifts in optimal forestry areas - Drought risk - Fire risk - Frost risk - Site

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Monitoring and Assessment of Drylands: Forests, Rangelands, Trees, and Agrosilvopastoral Systems. FAO Headquarters, Rome, Italy, 19-21 January 2015

© ICFR 2015

Page 8: Modeling risk on planted forests in South Africa · 2018-01-11 · Risk modeling • Climate change - Shifts in optimal forestry areas - Drought risk - Fire risk - Frost risk - Site

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Monitoring and Assessment of Drylands: Forests, Rangelands, Trees, and Agrosilvopastoral Systems. FAO Headquarters, Rome, Italy, 19-21 January 2015

© ICFR 2015

Page 9: Modeling risk on planted forests in South Africa · 2018-01-11 · Risk modeling • Climate change - Shifts in optimal forestry areas - Drought risk - Fire risk - Frost risk - Site

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Monitoring and Assessment of Drylands: Forests, Rangelands, Trees, and Agrosilvopastoral Systems. FAO Headquarters, Rome, Italy, 19-21 January 2015

© ICFR 2015

Remote sensing for monitoring Aridity Index:

MODIS 16 Data (Moderate Resolution Imaging Spectroradiometer, NASA) Modis data used to develop an Aridity Index based on Tsakiris & Vangelis (2005):

a = 1 Rainfall (P) = Potential Evapotranspiration (PET) a = 0 Drought

00.10.20.30.40.50.60.70.8

2000 2001 2002 2003 2004 2005 2006 2007 Long Term

Zululand - CoastalAridity Index

2000

2001

2002

2003

2004

2005

2006

2007

• Aridity Index • Stand growth (Diameter at Breast Height (DBH)

increase)

Page 10: Modeling risk on planted forests in South Africa · 2018-01-11 · Risk modeling • Climate change - Shifts in optimal forestry areas - Drought risk - Fire risk - Frost risk - Site

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Monitoring and Assessment of Drylands: Forests, Rangelands, Trees, and Agrosilvopastoral Systems. FAO Headquarters, Rome, Italy, 19-21 January 2015

© ICFR 2015

1,300 000

Page 11: Modeling risk on planted forests in South Africa · 2018-01-11 · Risk modeling • Climate change - Shifts in optimal forestry areas - Drought risk - Fire risk - Frost risk - Site

Monitoring and Assessment of Drylands: Forests, Rangelands, Trees, and Agrosilvopastoral Systems. FAO Headquarters, Rome, Italy, 19-21 January 2015

Current dominant species in SA plantation forestry

Pinus patula Pinus elliottii Pinus taeda

Eucalyptus grandis Eucalyptus nitens Eucalyptus smithii Eucalyptus grandis x Eucalyptus urophylla

Acacia mearnsii

Page 12: Modeling risk on planted forests in South Africa · 2018-01-11 · Risk modeling • Climate change - Shifts in optimal forestry areas - Drought risk - Fire risk - Frost risk - Site

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Monitoring and Assessment of Drylands: Forests, Rangelands, Trees, and Agrosilvopastoral Systems. FAO Headquarters, Rome, Italy, 19-21 January 2015

© ICFR 2015

Page 13: Modeling risk on planted forests in South Africa · 2018-01-11 · Risk modeling • Climate change - Shifts in optimal forestry areas - Drought risk - Fire risk - Frost risk - Site

Monitoring and Assessment of Drylands: Forests, Rangelands, Trees, and Agrosilvopastoral Systems. FAO Headquarters, Rome, Italy, 19-21 January 2015

Pests and pathogens

Case study: Leptocybe invasa (Eucalyptus gall wasp)

A major and growing threat to the forestry sector in South Africa

Linked to climate change } • Strongly climate driven •Susceptibility increased by physiological stress

Page 14: Modeling risk on planted forests in South Africa · 2018-01-11 · Risk modeling • Climate change - Shifts in optimal forestry areas - Drought risk - Fire risk - Frost risk - Site

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Monitoring and Assessment of Drylands: Forests, Rangelands, Trees, and Agrosilvopastoral Systems. FAO Headquarters, Rome, Italy, 19-21 January 2015

© ICFR 2015

• Climate change models indicate that South Africa is shifting towards drier

conditions

• Indigenous vegetation most affected: forest and grassland biomes

• Plantation forestry heavily affected

Loss in biodiversity, species

Sustainability at risk

Thank you