LANDCLIM project. Swedish Research Council

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LANDCLIM project Swedish Research Council Marie-José Gaillard 1, Shinya Sugita 2,1 Anna-Kari Trondman 1, Florence Mazier 3 Anne Birgitte Nielsen 4, Ralph Fyfe 5 Michelle Leydet 6 and LANDCLIM members* 1 Linnaeus University, Kalmar, Sweden 2 Tallinn University, Tallinn, Estonia 3 University of Toulouse, Toulouse, France 4 University of Göttingen, Göttingen, Germany 5 University of Plymouth, Plymouth, UK 6 University of Marseilles, Arbois, France

Swedish project: LANDCLIM 6000-200 LANDCLIM 6000-200 is a contribution to the IGBP-PAGES-Focus 4 PHAROS programme (www.pages.unibe.ch/science/focus4.html). The overall objective is to better understand vegetation/land use-climate interactions on long time scales, and to evaluate and fine-tune the regional climate model RCA3, the dynamic vegetation model (LPJGuess), and the coupled RCA3-LPJGuess model for better analysis of future climate change

Proposed scheme of GCMs model-data comparison RCA3 + Pollen data LJPGUESS GCMs Model-data comparison Gaillard et al. 2010, Clim Past

Testing REVEALS in southern Sweden Hellman et al. 2008a,b (JQS, VHA) Skåne Småland Storesjön (512 ha) Tenhultasjön (292 ha) Kansjön(77 ha) Vallsjön (707 ha) Coniferous Vombsjön(1224 ha) Sövdesjön (265 ha) Snogeholmssjön ( 240 ha) Börringesjön (274 ha) Krageholmssjön (186 ha) Trummen (76 ha) Deciduous Grassland Cultivated Built-up Lakes 0 20 40 60 80 km 0 25 50 75 100 km

Secale 2% Poaceae 19% Results Sweden: Skåne (Open Landscape) Observed vegetation (percentage cover) Skåne obse rv e d v e ge tation 26 taxa Rumex ace 3% Cerealia 41% Conifers Picea 13% Gaillard et al. 2010, Clim Past Pinus 3% Betula 3% Fagus 7% <1% Acer Carpinus Juniperus Fraxinus Tilia Ulmus Calluna Cyperaceae Filipendula Potentilla Ranunculus Rubiaceae Quercus 3% ~1% Alnus Corylus Salix Comp SF. Chic Plantago Deciduous trees Cerealia 4% Ulmus 2% Skåne re gional pollen perce ntages (20 samples), 26 taxa Rumex ace 2% Quercus 5% Pollen Percentages Poaceae 15% Fagus 13% Cerealia & Secale Corylus 3% Picea 3% Pinus 13% Betula 16% <1% Acer Juniperus Tilia Calluna Com p. CF. Chic Filipendula Potentilla Ranunculus Rubiaceae Alnus 16% 1% Carpinus Fraxinus Salix Cyperaceae Plantago Secale Poaceae & other nonarboreal plants

Secale 2% Poaceae 19% Results Sweden: Skåne (Open Landscape) Gaillard et al. 2010, Clim Past Observed vegetation (percentage cover) Skåne obse rv e d v e ge tation 26 taxa Rumex ace 3% Cerealia 41% Conifers Picea 13% Pinus 3% Betula 3% Fagus 7% <1% Acer Carpinus Juniperus Fraxinus Tilia Ulmus Calluna Cyperaceae Filipendula Potentilla Ranunculus Rubiaceae Quercus 3% ~1% Alnus Corylus Salix Comp SF. Chic Plantago Deciduous trees Cyperaceae 2% Comp. SF. Cich 5% Estimated vegetation using REVEALS Skåne estimated vegetation (20 samples), 26 taxa Secale 3% Poaceae 24% Cerealia & Secale Cerealia 32% Picea 7% Pinus 3% Alnus 4% Betula 2% Corylus 3% Rumex Fagus 10% Ulmus 2% <1% Acer Carpinus Juniperus Tilia Calluna Filipendula Plantago Potentilla Ranunculus Rubiaceae ~1% Fraxinus Quercus Salix Poaceae & other nonarboreal plants

Results Sweden: Småland (Semi-open Landscape) Observed vegetation (percentage cover) Pollen percentages Cerealia 5% Betula 6% Poaceae 18% Småland observed vegetation, 26 taxa Pinus 19% Picea Picea 44% <1% Acer Carpinus Fraxinus Juniperus Salix Tilia Ulmus Comp. CF. Chic Filipendula Plantago Potentilla Ranunculus Rubiaceae Secale ~1% Alnus Corylus Fagus Quercus Calluna Cyperaceae Rumex Betula 24% Corylus 2% Småland regional pollen percentages (20 samples), 26 taxa Quercus 2% Alnus 5% Poaceae 5% Picea 16% Pinus Pinus 42% <1% Acer Carpinus Fagus Fraxinus Salix Tilia Ulmus Calluna Comp. CF. Chic Cyperaceae Filipendula Plantago Potentilla Ranunculus Rubiaceae Secale ~1% Juniperus Cerealia Rumex Conifers Deciduous trees Hellman, Gaillard et al. 2008, JQS Cerealia & Secale Poaceae & other nonarboreal plants

Cerealia 5% Betula 6% Results Sweden: Småland (Semi-open Landscape) Observed vegetation (percentage cover) Poaceae 18% Småland observed vegetation, 26 taxa Pinus 19% Picea Picea 44% <1% Acer Carpinus Fraxinus Juniperus Salix Tilia Ulmus Comp. CF. Chic Filipendula Plantago Potentilla Ranunculus Rubiaceae Secale ~1% Alnus Corylus Fagus Quercus Calluna Cyperaceae Rumex Cerealia 9% Corylus 2% Betula 4% Estimated vegetation using REVEALS Alnus 2% Småland estimated vegetaiton, 26 taxa Poaceae 11% Pinus 13% Picea Picea 54% <1% Acer Carpinus Fagus Fraxinus Juniperus Ulmus Calluna Filipendula Plantago Potentilla Ranunculus Rubiaceae Rumex Secale ~1% Quercus Salix Tilia Comp. CF. Chic Cyperaceae Conifers Hellman, Gaillard et al. 2008, JQS Deciduous trees Cerealia & Secale Poaceae & other nonarboreal plants

The LANDCLIM project North-western and Western Europe North of the Alps PPE Mosspolsters 7 sites PPE Lakes 3 sites Study area The area for which we have Pollen Productivity Estimates (PPEs): for 34 taxa in total Spatial scale of REVEALS reconstructions: ca. 100 km x 100 km CHOSEN GRID: 1 x 1 Broström et al. 2008, VHA 17

Responsibles for data collecting and REVEALS runs Coordinator: MJ Gaillard Gaillard et al. 2010, Clim Past Model development and programs: Shinya Sugita A.K. Trondman, M.-J. Gaillard F. Mazier A.B. Nielsen and T. Giesecke R. Fyfe A. Bjune HJB Birks EPD: M. Leydet T. Alenius M Kangur L. Kalnina et al Lauras B. M. Latalowa P. Kunes(PALYCZ) J. Lechterbeck(Personal data) P. Van der Knaap(ALPADABA)

REVEALS runs - PROTOCOL In order to lower the number of REVEALS runs, maximize the number of pollen records used, and ensure good-quality REVEALS reconstructions: Test of the effect of different input data on the REVEALS estimates using the pollen data base from the Czech Republic (Kunes et al.), using the Spearman rank correlation test (Mazier et al. in prep.) Note: The Spearman rank corr. test compares the ranking of PFTs abundance, it does not compare absolute values.

What pollen records? What taxa? How many taxa? What PPEs? -Bogs or lakes? -Large or/and small sites? -Chronology: -how many dates used for the age-depth model? -All taxa with PPEs or selected taxa? -All PPEs (means) or selected PPEs? RESULTS: IN GENERAL, THERE ARE NO SIGNIFICANT DIFFERENCES BETWEEN THE REVEALS ESTIMATES IN TERMS OF TAXA RANKING USING THE DIFFERENT ALTERNATIVES Mazier et al. in prep

FIRST PRODUCT Trondman et al. Unpublished, in prep. 2011 25 selected taxa (true entomophilous taxa excluded) Lakes and bogs small ( 10 ha) and large sites ( 50-100 ha), i.e. ALL SITES 3 dates for age-depth chronology For each taxon, mean of all PPEs available in the study area

PROTOCOL: 1st product 1) PPEs for 36 taxa, 25 selectedtaxa; 2) for each taxon: 1-6 PPE values; use the mean value Reference taxon Generally > 95% of total sum of terrestrial taxa Gramineae GRASSES Herb taxa Apiaceae Artemisia DRY MEADOWS, WEED Calluna vulgaris HEATHER - FOREST UNDERSTOREY, BOGS or HEATHS (PASTURELANDS) Cerealia-t CEREALS (AGRICULTURE) Comp. SF. Cichorioideae Cyperaceae SEDGES MEADOWS (WET, FRESH, DRY), FENS or BOGS Empetrum Ericaceae Filipendula FRESH, WET MEADOWS Leucanthemum (Anthemis-t) Plantago lanceolata MEADOWS, PASURELANDS, WEED Plantago media Plantago montana Potentilla-t Ranunculus acris-t Rubiaceae Rumex acetosa-t MEADOWS, PASTURELANDS, WEED Tree Taxa Abies FIR Acer Alnus ALDER Betula BIRCH Carpinus HORNBEAM Corylus HAZEL Fagus BEECH Fraxinus ASH Juniperus JUNIPER Picea SPRUCE Pinus PINE Quercus OAK Salix WILLOW Tilia LINDEN Ulmus ELM Secale-t RYE (AGRICULTURE) Trollius Vaccinium

Two priorities within the project: 3) Time periods Priority 1 The Time-window sites for comparison with climate model (VR LANDCLIM project) + other purposes (LUCCI, Lund, Anna Broström) 0-100 cal BP; 1850-x AD modern time-window 100-350 cal BP; 1600-1850 AD 200 cal BP time-window 350-700 cal BP; 1250-1600 AD 600 cal BP time-window 2700-3200 cal BP; 1250-750 BC 3000 cal BP time-window 5700-6200 cal BP; 4250-3750 BC 6000 cal BP time-window Priority 2 The Holocene trajectories for comparison with vegetation model 10 selected target areas in the study region, covering the entire Holocene (or at least the last 7000 years)

4) Plant Functional Types (PFTs) REVEALS estimates are calculated for 25 taxa; they are then grouped into - 10 PFTs (LPJGUESS), and 3 broad plant groups (RCA3) Land-cover types Evergreen Summergreen Openland 1 Picea 2 Abies Pinus Juniperus Salix Calluna Carpinus, Fagus, Tilia, Ulmus

Uncertanties and problems to think about Uncertainties: 1-2 small sites in one grid cell: very uncertain reconstruction Large bogs: vegetation growing on the bog may strongly bias the reconstruction Problems: Open land PFTS: many taxa may belong to natural or human-induced vegetation types Gramineae Cyperaceae Calluna

ONE EXAMPLE of map of REVEALS estimates for spruce Trondman et al unpublished, in prep 2011

Collaboration with ALCC modellers Gaillard et al. 2010, Clim Past (reprints) With Jed Kaplan (start 17th of January!) Compare ALCC and REVEALS estimates in NW Europe at the large spatial scale 100 km x 100 km: project started Compare ALCC and LOVE estimates in southern Sweden at the small spatial scale ca. 500 m to 5 km radius (= relevant source area of pollen (RSAP), depending on the site and structure/grain of vegetation): future project

Sum of PFTs GL and AL: for comparison with Kaplan et al. 2009 UNPUBLISHED, in prep 2011 AD 1850-1950 AD 1550-1850 AD 1250-1550 1000 BC 4000 BC

EXAMPLES of COMPARISON Kaplan s KK10 scenarios and REVEALS estimates Kaplan et al. unpublished, in prep 2011

Conclusions The various spatially explicit descriptions of past natural and human-induced land-cover available todate exhibit very large discrepancies First pollen-based land-cover reconstructions are now available for many areas of W Europe N of the Alps (LANDCLIM research project) The advantage of REVEALS reconstructions is that they provide cover of plant taxa rather than forest, croppasture, or crop fractions The REVEALS estimates are an important step forward to validate the ALCC scenarios A first comparison with Kaplan s scenarios show a fairly good agreement between REVEALS estimates and the modeled ALC Next steps: model-data comparison using the REVEALS estimates; comparison with LPJGuess runs, use in the RCA3 runs.