Forest damage in a changing climate Anna Maria Jönsson and Lars Bärring Dept. of Physical Geography and Ecosystem Analysis Geobiosphere Science Centre, Lund University

Forest damage in a changing climate Predisposing factors Climate change, Tree species and Provenances Forest management, Nutrient availability, Air pollution Triggering factors Weather events exceeding tree acclimatization capacity Often causing visible damage Contributing factors Attacks by pests and pathogens Often the cause of mortality

Extreme weather event ≠ Extreme situation for the tree Acclimatization The ability to adjust to changing weather conditions Tolerate non-optimal conditions Threshold values could be more important than extreme values Affected by Example Seasonality Spring backlashes Intensity Flooding Duration Dry spells Frequency Wind storms Combination Spring frost followed by drought

Tree nutrient availability decomposition, weathering, mycorrhiza, leakage Climate change temperature dry spells during summer flooding episodes storm frequency Tree damage frost damage drought stress root oxygen deficiency wind throw, root damage CO2 Pests and Pathogens Photosynthesis: growth - repair - defence - respiration NPP +10-20%

Ongoing activities within ENSEMBLES related to task 6.2.2, 6.2.3, 6.2.5 and 6.2.10 Spring backlash index: Frost damage projections SBI has been calculated for Sweden, is currently applied to European conditions using the PRUDENCE dataset, and will use ENSEMBLES RCM data. A Frost hardiness and damage sub-module is incorporated to the vegetation model LPJ-GUESS. 2) Modelling the temperature dependent development of the spruce bark beetle Ips typographus The model has been applied to south Swedish conditions, and will be applied for Northern European spruce forests using ENSEMBLES RCM data.

Start of dehardening in Norway spruce 5 consecutive days with a mean temperature above 5°C 1961-1990 Scenario B2 Scenario A2 1 2 3 4 5 month Climate data: HadRM3

Frost events after the start of dehardening over 30-years Control period Scenario B2 - Control Scenario A2 - Control 0 100 200 Number of events -75 0 75 Difference

Temperature dependent annual cycle of Ips typographus Egg development Summer swarming? > Spring swarming Egg development? Winter mortality Almost 100% for not completely developed bark beetles

Development of Ips typographus in Växjö April May June July August September 1961-1990 Scenario B2 Scenario A2 Spring swarm Completed development

Temperature dependent summer swarming of Ips typographus 1961-1990 1981-2010 2011-2040 Data from RCA3 Scenario A2 2041-2070 2071-2100