Research on Ecosystem stability and transitions at PIK
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1 Research on Ecosystem stability and transitions at PIK Kirsten Thonicke Speaker of the working group Ecosystem stability and transitions in the Research Domain Earth System Analysis Deputy Chair of Research Domain Potsdam Institute for Climate Impact Research (PIK) 1
2 Potsdam Institute for Climate Impact Research (PIK) Founded in 1992 One of the important institutes in climate impact research Participates in IPCC Assessment and special reports, e.g. leading WGIII in IPCC AR5 Science is designed for stakeholder interaction and policy recommendation Consists of 4 research domains RD1 Earth System Analysis RD2 Climate Impacts and Vulnerability RD3 Sustainable Solutions RD4 Transdisciplinary Concepts and Methods 2
3 Ecosystem stability and transitions at PIK Our research focuses on the following aspects Functional diversity, elasticity of ecosystems and ecological tipping points Impacts of extreme events and (fire) disturbances on ecosystems Shifts in ecosystem services, role of natural vegetation and climate regulation services Team members: Delphine Zemp, Kirsten Thonicke, Werner von Bloh, Alice Boit, Finn Müller-Hansen, Catrin Ciemer, Ana Cano Crespo, Boris Sakschewski, Fanny Langerwisch (from left to right) 3
4 Importance of the Amazon biome 10 to 15% of world biodiversity Stores Billion t carbon = % of global carbon storage Giant atmospheric moisture pump: 25-50% of received precipitation recycled 20 Mio t per day transpired to the atmosphere contributes 19 % to precipitation to La Plata Basin NASA Amazon river discharges 15 % of freshwater input into the oceans 17 Mio tonnes per day 4
5 Giant atmospheric moisture pump IRTG project: Delphine Zemp IMPORTANCE OF CASCADING MOISTURE RECYCLING IN SOUTH AMERICA 5
6 Input 1 Input 2 Period Precip. TRMM Average CRU, GPCC, GPCP, CPC Atmospheric moisture tracking model (WAM- 2layers*) Evap. MODIS LandFlux- Eval Wind Humidity ERA-Interim Amount and direction of recycled moisture from the origin (evapotranspiration) to the destination (precipitation) * van der Ent (Water Res. Res., 2010), van der Ent (Earth Sys. Dyn. 2014) 6
7 Fraction of the evapotranspiration in the Amazon basin that contributes to rainfall over the La Plata basin during the wet season: 11-16% through direct moisture recycling 16-23% Amazon basin through cascading moisture recycling Fig. Key intermediary region as identified by using clustering coefficient, a measure from complex network analysis 18-23% Intermediary 6% through cascading moisture recycling through direct moisture recycling Fraction of the total rainfall over the La Plata basin that comes from the Amazon basin during the wet season: La Plata basin 7
8 Fraction of evapotranspiration that precipitates over the La Plata basin through direct and cascading moisture recycling (a) Direct (b) Cascading The southern part of the Amazon basin is not only a source of moisture but also an intermediary region that distributes moisture from the entire basin! 8 Zemp et al. (Atmos. Chem. Phys. Discuss., 2014).
9 Fire Deforestation and land-use change Climate change Amazon basin IRTG project: Ana Cano-Crespo FIRE IN DIFFERENT LAND USE TYPES 9
10 Fire in the Amazon region Fire used in deforestation process in the Amazon Spatial overlay of coarseresolution data How is fire used in land management? Aragao et al. Science 2010: spatial hotspots moving away from deforestation to agriculture Can we confirm this relationship using highresolution land-cover data? 10 Aragao et al. Science 2010
![Area burnt per land-cover type 2008 State Mato Grosso Pará Rondônia Total area burnt [km²] 29100 3420 760 % of state 3.2 0.3 0.3 Mato Grosso 1.5% 3% 5% 6% Pará 7% 5% 6.](/docs-images/79/79508668/images/11-2.jpg "5% 4% 35% Rondônia 9% 2% 1% 2% 8% 26% 10% 10% 82% 10% 22% 18% 22% Forest Pasture Non-forest Secondary vegetation Pasture+sparse bushes Regeneration Water Agriculture Deforestation Farms Urban")
11 Area burnt per land-cover type 2008 State Mato Grosso Pará Rondônia Total area burnt [km²] % of state Mato Grosso 1.5% 3% 5% 6% Pará 7% 5% 6.5% 4% 35% Rondônia 9% 2% 1% 2% 8% 26% 10% 10% 82% 10% 22% 18% 22% Forest Pasture Non-forest Secondary vegetation Pasture+sparse bushes Regeneration Water Agriculture Deforestation Farms Urban Non-observed Mines Others Pasture+bare soil Cano-Crespo, A., P. J. C. Oliveira, A. Boit, M. Cardoso, and K. Thonicke (2015), 11 Forest edge burning in the Brazilian Amazon promoted by escaping fires from managed pastures, J. Geophys. Res. Biogeosci., 120, , doi: /2015jg
12 Pasture fires contribute 30-55% to forest fires Burned forest (%) Burned area FOREST PASTURE Burned area Mato Grosso 1-km Pará 2-km Rondônia Cano-Crespo, A., P. J. C. Oliveira, A. Boit, M. Cardoso, and K. Thonicke (2015), 12 Forest edge burning in the Brazilian Amazon promoted by escaping fires from managed pastures, J. Geophys. Res. Biogeosci., 120, , doi: /2015jg
13 Fire Deforestation and land-use change Climate change Amazon basin River Hydrology Study: F. Langerwisch (PIK) IMPACT OF Carbon storage CLIMATE & LAND USE CHANGE ON THE AMAZON RIVER 13
14 Amazon basin: productive forest connected to huge river basin Foto: F.Langerwisch Erosion Foto: F.Langerwisch Very productive forest with dead organic material Foto: F.Langerwisch Regular flooding - inundation 14
15 Impacts of future climate change on inundation patterns Changes in future temperature and precipitation on inundation pattern NW Amazonia experiencing longer time with inundated flood plains Forest not adapted! SE Amazonia experiencing shorter time with inundated flood plains Impacts on fishing Seed distribution Carbon dynamics (transport from forest to river, export to Atlantic ocean) Lengthening (blue) and shortening (red) of duration of inundation in months (mean over 24 model realisations) between future (2070 to 2099) and reference (1961 to 1990) period. Langerwisch F, Rost S, Gerten D, Poulter B, Rammig A, Cramer W 2013 Potential effects of climate change on inundation patterns in the Amazon basin. Hydrol. 15 Earth Syst. Science, 17: , doi: /hess
16 Riverine carbon model RivCM Proportion of dead organic matter (as simulated by the LPJmL DGVM) exported to the river during flooding Within the river body decomposition of particulate organic carbon (POC) and dissolved organic carbon (DOC) both respired within the water body Outgassed to the atmosphere as CO 2 POC and DOC exported to the ocean 16
17 Climate change and effects of deforestation on future riverine carbon dynamics Climate change influences carbon dynamics in Amazon river Higher productivity increases dead biomass and export to river More carbon outgassed from river Less in river discharge to Atlantic ocean Langerwisch F, Walz A, Rammig A, Tietjen B, Thonicke K, Cramer W (2016), Climate change increases riverine carbon outgassing, while export to the ocean remains uncertain, Earth Syst. Dynam., 7, , doi: /esd
18 Fire Deforestation and land-use change Climate change Amazon basin Biomes Study: A. Boit (PIK) Carbon storage IMPACT OF CLIMATE & LAND USE CHANGE ON SOUTH AMERICAN BIOMES 18
19 Future anthromes formation and climate change impacts Considering changes in land cover and climate change Applying LPJmL DGVM to climate change scenario RCP 2.6 and SSP1 vs RCP8.5 and SSP5 And combine it with Land use change scenario simulated by CLUE Most land-cover change happened during historic time and anthromes remain during 21 st century Climate change impacts cause loss of natural biome in eastern Amazon Boit A, Sakschewski B, Boysen L, Cano-Crespo A, Clement J, Alaniz NG, Kok K, Kolb M, Langerwisch F, Rammig A, Sachse R, van Eupen M, von Bloh W, Zemp D and Thonicke K (2016), Large-scale impact of climate change versus land-use change on future biome shifts in Latin America. Glob Change Biol., Doi: /gcb
20 Fire Deforestation and land-use change Climate change Biodiversity Additional study: B. Sakschewski Carbon storage ROLE OF BIODIVERSITY FOR ECOSYSTEM RESILIENCE 20
21 Flexible Individual Traits in LPJmL Sakschewski B, von Bloh W, Boit A, Rammig A, Kattge J, Poorter L, Peñuelas J and Thonicke K (2015) Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model, Global Change Biology, DOI: /gcb
22 400ha of site in Ecuador RCP 8.5 HadGEM shuffling climate of from 2100 onwards High diversity LPJmL-FIT Low diversity LPJmL-FIT Standard LPJmL Gap model 2 PFTs 22
23 Trait range allows the better adapted trees to take over and recover biomass High diversity Low diversity Sakschewski et al. NCC
24 Thanks to all colleagues who contributed to this work with ideas, comments and suggestions and thank you for your attention!
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