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Modeling local response of vegetation from regional climate scenarios

Modeling local response of vegetation from regional climate scenarios. Uno Wennergren Linköping University Anna Cabraijic Umeå University Kristina Palmqvist Umeå University Part of PhD Thesis of Anna C, June 2009. Structure. Question Results Method Detailed Result

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Modeling local response of vegetation from regional climate scenarios

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  1. Modelinglocalresponse of vegetation from regional climate scenarios Uno Wennergren Linköping University Anna Cabraijic Umeå University Kristina Palmqvist Umeå University Part of PhD Thesis of Anna C, June 2009

  2. Structure • Question • Results • Method • DetailedResult • Discussion - Conclusions

  3. Question! • Ifweknowhow a species physiology/growthdepend on: • Temperature (air temperature, T(t)) • Humidity (air relative humidity, RH(t)) • Light (irradiance, I(t)) Can wepredict the response to climatechange?

  4. Temperature • Humidity • Light Lichen: PlatismatiaGlauca Näverlav VariedRagLichen Widelyspread inconiferforest Epiphytic Fungus + Green algal Green algaldirect respons to humidity Cold Humid or Dry Light or Dark Varm Humid Light Varm Humid Dark Varm Dry Dark or Light Energy 0 + - 0 photosynthesis respiration

  5. RH(t) T(t) I(t) RH(t) T(t) I(t)

  6. Study:Twoyearlygrowthpatterns of lichens:2070-2100 scenario SRES A2 2070-2100 scenario SRES B2 relatively1971-2000 referenceclimatelocaltimeseries 1993/94 Results: • Interiorlichens: • reduced to unchangedyearlygrowth • Exposed lichens: • increasedgrowth RH(t) T(t) I(t) RH(t) T(t) I(t)

  7. Moredetails • Functions: • Net Photosynthesis: NP(I(t),T(t),RH(t)) • Respiration: R(I(t),T(t),RH(t)) • Water content WC(T(t),RH(t)) • Parameterized by data on I(t),T(t),RH(t) and NP, R , WC • Laboratory C02exchange data • Fieldmicro-climate data 1993/94 • Growth of lichens

  8. Moredetails • Functions: photosynthesis and respiration • Regional climatechange: • Transforming the time series of Micro – climates SRES A2, 2070-2100: I(t) T(t) RH(t) MeasuredInterior 93/94: I(t) T(t) RH(t) SRES B2, 2070-2100: I(t) T(t) RH(t) SRES A2, 2070-2100: I(t) T(t) RH(t) Measured Exposed 93/94: I(t) T(t) RH(t) SRES B2, 2070-2100: I(t) T(t) RH(t) Sixyearlygrowth pattern from different microclimates

  9. Moredetails • Functions: photosynthesis and respiration • Regional climatechange to 6 Micro – climates: • Combiningmicro- regional- climate data Temp June exposed Humidity June exposed Light June exposed Measured Micro-climate 24h Light June interior

  10. Moredetails • Functions: photosynthesis and respiration • Regional climatechange to 6 Micro – climates: • Combiningmicro- regional- climate data Temp June exposed Regional data (Västerbotten): Monthlymean and variances : I(t), RH(t), T(t) 1971-2000 reference 2070-2100 SRES A2 2070-2010 SRES B2 Difference in mean and variance betweenReference and SRES Applied to measuredtimeseries Preservinglocal pattern Changingmean and variances absolute changetemperature relative changehumidity and light Humidity June exposed Light June exposed

  11. Moredetails • Functions: photosynthesis and respiration • Regional climatechange to 6 Micro – climates: Temp June exposed A2 B2 Humidity June exposed Ref Light June exposed

  12. Moredetails • Functions: photosynthesis and respiration • Regional climatechange to 6 Micro – climates: Temp June exposed A2 B2 Humidity June exposed Ref Light June exposed

  13. RH(t) T(t) I(t) Conclusions: Vegetation – climatechange – tiltedearthaxis Expect a largerlocalthanregional redistribution of species. Lichens and vascular plants and… RH(t) T(t) I(t)

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