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Projections des impacts du changement climatique sur les fore ̂ ts : quelles stratégies d'adaptation face à des incertitudes considérables ? Paul Leadley.

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Presentation on theme: "Projections des impacts du changement climatique sur les fore ̂ ts : quelles stratégies d'adaptation face à des incertitudes considérables ? Paul Leadley."— Presentation transcript:

1 Projections des impacts du changement climatique sur les fore ̂ ts : quelles stratégies d'adaptation face à des incertitudes considérables ? Paul Leadley Laboratoire ESE Université Paris-Sud Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010

2 Sources of uncertainty in projections 1. Développement Socio-économique 2. Déterminants de la biodiversité Ex : climat, usage des sols, gestion des ressources génétiques, etc. 3. Etat de la biodiversité Ex : diversité génétique, diversité des especes, communautés, paysages 4. Services Ecosystémiques Ex : provisioning, regulating, sustaining and cutural services 5. Réponses: Atténuation Adaptation Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010

3 Model projections of climate change impacts on French forests Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010

4 #LaboratoireSitePI 1ESE, UMR Univ. Paris-Sud / CNRS / ENGREFOrsayPaul LEADLEY 2FGEP, INRAClermont- Ferrand Jean-François SOUSSANA 3ISEM, UMR Université Montpellier II / CNRSMontpellierChristine DELIRE 4CEFE, UMR CNRS / Univ. Montpellier I,II,III / CIRAD / ENSAM MontpellierIsabelle CHUINE 5BIOGECO, UMR CNRS / Univ. Bordeaux 1BordeauxAntoine KREMER 6Arboretum National des Barres, ENGREFNogentStephanie BRACHET 7LECA, UMR CNRS / Université Joseph Fourier GrenobleSandra LAVOREL 8Ecologie et Ecophys. Forestières, UMR INRA / Université Nancy NancyJean-Luc DUPOUEY 9LSCE, UMR CEA / CNRSGif-sur-YvetteNathalie DE NOBLET- DUCOUDRE 10UMR & USM CNRS / MNHN / Conservatoire Botanique National du Bassin Parisien ParisNathalie MACHON ANR QDiv: Quantification des effets des changements globaux sur la diversité végétale Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010

5 Projecting potential shifts in tree ranges in response to climate change: an intermodel comparison approach to qualifying and quantifying uncertainty Alissar Cheaib 1, Christophe François 1, Vincent Badeau 2, Isabelle Chuine 3, Christine Delire 4, Eric Dufrêne 1, Emmanuel Gritti 3, Wilfried Thuiller 5, Nicolas Viovy 6 and Paul Leadley 1 1 Laboratoire dÉcophysiologie Végétale, UMR dÉcologie, Systématique et Évolution CNRS 8079, Université Paris- Sud XI Orsay Cedex France 2 UMR 1137, INRA UHP, Forest Ecology and Ecophysiology, Phytoecology Team, route de la Forêt-dAmance, Champenoux, France 3 Centre dEcologie Fonctionnelle et Evolutive, Equipe BIOFLUX, CNRS, 1919 route de Mende, Montpellier cedex 4 CNRS Meteo-France – Toulouse, France 5 Laboratoire d Écologie Alpine, UMR CNRS 5553, Université´ J. Fourier, BP 53, Grenoble Cedex 9 France 6 Laboratoire des Sciences du Climat et de lEnvironnement, CEA/ CNRS, Saclay, France. Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010

6 Treating UNCERTAINTY in modeling climate impacts on forests: an example from the ANR QDiv project High resolution (8 km) climate scenarios Collaboration with CERFACS (L. Terray) High resolution (8 km) maps of current tree distributions Collaboration IFN (C. Cluzeau) High resolution maps of key soil properties Furnished by INRA Orléans A broad range of models of tree response to climate change Niche Based BIOMOD NANCY-NBM STASH Phenology-based PHENOFIT DGVM Orchidée (PFT) IBIS (PFT) LPJ-Guess (Species) Mechanistic Tree growth CASTANEA E.g., Simulated mean August temperatures in 2098 E.g., current distribution of Fagus sylvatica (Common beach) Assessment of climatic risk for: Quercus robur Quercus petraea Fagus sylvatica Pinus sylvestris Quercus ilex + Plant functional groups

7 A broad range of modelling concepts: 7 Models Mechanistic approaches « Niche - Based » Models or « Bioclimate envelope » Models ORCHIDEE (Krinner et al, N. Viovy CEA) PHENOFIT (Chuine and Beaubien I. Chuine, CEFE Montepellier) CASTANEA ( E. Dufrêne et al, C. François and A. Cheaib, ESE Orsay) Correlative approaches Nancy NBM (V. Badeau, INRA Nancy) BIOMOD (W. Thuiller, W. Thuiller, Grenoble) STASH (Sykes et al, E. Gritti, CEFE Montpellier) « Phenology – Based » Model Tree C balance and Growth Dynamic Global Vegetation Models (DGVMs) IBIS (Kucharik et al, C. Delire Meteo France) LPJ (Stich et al, E. Gritti, CEFE Montpellier)

8 Climate scenario (regionalized Arpège) : The A1B Story line Time Slice Time Slice Time Slice ~ 8989 pixels in France: Spatial resolution 8Km x 8Km (L. Terray, CERFACS, Meteo France) TS1 TS2 TS Average CO °C mean temperature increase mm/year decrease in precipitation CO 2

9 Fagus sylvatica European beech Hêtre commun Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010

10 Current distribution simulations and model evaluation Fagus sylvatica Current distribution (IFN) BIOMODNancy NBMSTASH TSS = 0.73 TSS = 0.66TSS = 0.18 PHENOFIT CASTANEALPJ TSS = 0.16 TSS = 0.33 TSS = 0.48 TSS = Sensitivity + Specificity - 1 Sensitivity = True presence / (True presence + false absence) Proportion of observed presences that are predicted as such: quantifies omission errors Models Evaluation: True Skill Statistic (TSS) method (Allouche et al, 2006) Specificity = True absence / (True absence + false presence) Proportion of observed absences that are predicted as such: quantifies commission errors

11 0: No forest 1: Absence 2: Presence V Saône Alsace Vosges Alps Jura NE NW SW Pyrenees Center Brittany Average response 48 % % % 100 % 58 % 70 % 99% 53 % % 75 % % Fagus sylvatica 2050 Projections of distribution Y axis (Sum Sum Current) Sum Current

12 V Saône Alsace Vosges Alps Jura NE NW SW Pyrenees Center Brittany Average response 48 % % % 100 % 58 % 70 % 99% 53 % % 75 % % : No forest 1: Absence 2: Presence Fagus sylvatica 2050 Projections of distribution Y axis (Sum Sum Current) Sum Current

13 V Saône Alsace Vosges Alps Jura NE NW SW Pyrenees Center Brittany Average response 48 % % % 100 % 58 % 70 % 99% 53 % % 75 % % : No forest 1: Absence 2: Presence Fagus sylvatica 2050 Projections of distribution Y axis (Sum Sum Current) Sum Current

14 Fagus sylvatica Tests of mechanisms (TS2-TS1)/TS1 AlpsNE CASTANEA LPJ Current CO2 (TS2-TS1)/TS1 Alps NE PHENOFIT (TS2-TS1)/TS1 Current Rainfall Examples BIOMOD NE (TS2-TS1)/TS1 Jura Current Temp PHENOFIT Alsace CASTANEA V Saône Current Temp 2050 Temp 2050 Temp 2050 Rainfall Niche models show a strong negative response to warming, this response is weaker or even reversed in mechanistic models Mechanistic models are very responsive to reductions in precipitation Rising CO 2 offsets negative climate change impacts in mechanistic models (not accounted for in niche models) 2050 Rainfall Current Rainfall 2050 CO CO2 Current CO2

15 Bioclimatic-envelope models do a remarkably good job of simulating current distributions, in some cases with as few as three climate parameters. Bioclimatic-envelope models project nearly complete loss of favorable climate in the plains of France by 2050 for this A1b climate scenario and average soils. This appears to be driven largely by high sensitivity to climate warming. Mechanistic models project small or moderate losses of favorable climate in the plains and increased range in mountains. Most models project increased productivity in the Northern plains and mountains (not shown). Rising CO 2 plays a key role in counteracting negative effects of climate change. Recent observations and experiments tend to side with mechanistic models, but hidden or long-term effects (e.g., competition, disease, regeneration) might explain current and future distributions as simulated by bioclimatic models Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010 Beech: Take home messages

16 Pinus sylvestris Scots pine Pin sylvestre Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010

17 Current distribution simulations and model evaluation Pinus sylvestris Current distribution (IFN) BIOMODNancy NBM TSS = 0.48TSS = 0.25 STASH PHENOFITLPJ TSS = 0.30 ORCHIDEEIBIS TSS = 0.26 TSS = 0.07TSS = 0.03 Needleleaf Evergreen

18 0: No forest 1: Absence 2: Presence Alps Jura V saône Vosges Alsace NE NW Brittany SW Pyrenees Center 68 % Average models % % 49 % 72 % % 41 % % % 35 % % Pinus sylvestris Projections for 2050 Y axis (Sum TS2-SumTS1) SumTS1

19 Pinus sylvestris LPJ BIOMOD (TS2-TS1)/TS1 Vosges (TS2-TS1)/TS1 PHENOFIT Vosges NE T°C TS1 NE PHENOFIT LPJ (TS2-TS1)/TS1 Vosges (TS2-TS1)/TS1 NE All models are highly sensitve to warming All models are relatively insensitive to reductions in precipitation Rising CO 2 attenuates climate change impacts in mechanistic models Tests of mechanisms Current Temp 2050 Temp Current Rainfall 2050 Rainfall Current CO CO2

20 Current distributions are difficult to simulate, in part due to use of Scots pine outside its natural range All models project substantial loss of favorable climate in the plains of France by 2050 for this A1b climate scenario and average soils. This is driven by high sensitivity to climate warming in all models. Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010 Scots Pine: Take home messages

21 Quercus ilex holm oak chêne vert Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010

22 Quercus ilex 0: No forest 1: Absence 2: Presence BIOMOD 2050 NBM NancySTASH 2050 LPJ 2050 ORCHIDEEIBIS 2050 Evergreen Broadleaf

23 Forest plant diversity Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010

24 Identifier des modifications en cours de laire de distribution des espèces au travers des relevés de lInventaire forestier national (IFN). – J-L Dupouey, V Badeau (EEF, INRA Nancy) Evolution de la composante méditerranéenne de la végétation forestière entre 1990 et 2100 selon le scénario climatique Arpège B2 de Météo-France. Current Statistical model based on IFN and AURELHY climate data 2100 Projected distrubution Arpège B2 Climate simulation + Statistical distrubution model

25 Adaptation: What to do in the face of uncertain impacts? Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010

26 Adaptation of French forests to climate change An ONF/INRA manual of management techniques to limit climate change impacts on forests Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010

27 Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010

28 Reinforce natural processes to increase resilience Reduce exposure to climate change Plant species or genotypes, including introduced species, that are more tolerant of projected changes in climate Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010 Examples of adaptive management strategies

29 Reinforce natural processes to increase resilience Increase the use of mixed species stands Maintain or increase genetic diversity, e.g., through natural regeneration rather than the planting of clones Respect knowledge of tree ecology (e.g., soils, climate) Avoid soil compaction during forestry activities Reduce evapo- transpiration through management of leaf area Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010

30 Reduce exposure to climate change Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010 Old growth Douglas fir

31 Reduce exposure to climate change Reduce rotation times. Shift to fast growing trees (esp. conifers) or to coppice plantations (if 2 nd generation biofuels take off, GM trees are permitted). Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010 Douglas fir (Pseudotsuga sp.) plantation Coppice poplar plantation

32 Plant species or genotypes that are more tolerant of predicted changes in climate Introduce new drought and heat tolerant species and genotypes, i.e., introduced species and possibly GM trees. Use transplants exploiting the natural differences in genotypes across species range Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010 Eucalyptus plantationUse provenance trials and other information to identify pre-adapted genotypes, e.g., lodgepole pine in W. Canada (ONeill et al. 2007, Wang et al. 2010)

33 Plant species or genotypes, including introduced species, that are more tolerant of projected changes in climate Introduce drought and heat tolerant species, possibly including GM trees. Use transplants exploiting the natural differences in genotypes across species range Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010 Eucalyptus plantationUse provenance trials and other information to identify pre-adapted genotypes, e.g., lodgepole pine in W. Canada (ONeill et al. 2007, Wang et al. 2010)

34 There is a tremendous need to improve biodiversity scenarios and their use in management and political decision making Regardless of the advances in scenarios we will face difficult choices for forest management in the face of very large uncertainties Laboratoire dEcologie, Systématique et Evolution ACC – Paris, Sept 2010 Conclusions

35 15-16 Sept, Paris

36 The way forward Programme Phare: Modélisation et scénarios de la biodiversité Humboldt project

37

38 0: No forest 1: Absence 2: Presence Alps Jura V Saône Alsace Vosges NE NW Brittany SW Pyrenees Center 15 % % % % % % 80 % % 78 % % Average models Quercus robur Y axis (Sum TS2-SumTS1) SumTS1

39 Quercus robur Hypothesis: Tests TS2 Climate T°C of TS1 TS2 Climate 1 2 Rainfall of TS1 TS2 Climate 3 CO 2 TS1 Examples BIOMOD NE (TS2-TS1)/TS1 PHENOFIT T°C TS1 V Saône NE Rainfall TS1 PHENOFIT Rainfall TS1 (TS2-TS1)/TS1 BIOMOD CO2 TS1 Alps LPJ (TS2-TS1)/TS1 NE CO2 TS1 Quercus robur Jura T°C TS1 LPJ Jura T°C TS1 LPJ (TS2-TS1)/TS1 NE T°C TS1

40 0: No forest 1: Absence 2: Presence Alps Jura V Saône Alsace VosgesNE NW SW Brittany Pyrenees Center 85 % % % % % % 61 % % % 79 % % Average models TeBS Y axis (Sum TS2-SumTS1) SumTS1

41 Temperate Broadleaf Summergreen TS2 Climate T°C of TS1 TS2 Climate 1 2 Rainfall of TS1 TS2 Climate 3 CO 2 TS1 BIOMOD ORCHIDEE CO2 TS1 Alps (TS2-TS1)/TS1 NE CO2 TS1 ORCHIDEE (TS2-TS1)/TS1 AlpsNE Rainfall TS1 (TS2-TS1)/TS1 ORCHIDEE Alps T°C TS1 NE T°C TS1 (TS2-TS1)/TS1 AlpsNE T°C TS1


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