Pushing the limits: Climate and Range Distribution of Two Forest - PowerPoint PPT Presentation

1 Pushing the limits: Climate and Range Distribution of Two Forest Pests *****Colloque présenté en anglais***** Kishan Sambaraju, chercheur scientifique Modélisation des épidémiologies RNCan-SCF-CFL

2 Pushing the limits: Climate and range distributions of two forest pests Kishan Sambaraju, Ph.D. Natural Resources Canada Canadian Forest Service

3 Quote “A scientific man (sic) is the only person who has anything to say and does not know how to say it” Un scientifique est la seule personne qui a des choses à dire, mais ne sais pas comment les dire (parfaitement en français)

4 Outline 1. Climate change 2. Climate vs. Forest pest distributions • Empirical modelling • Dendroctonus ponderosae • Ceratocystis polonica • Trends Dendroctonus ponderosae • 3. Summary

5 Climate Change • What is it? • Long-term changes in temperature and precipitation patterns Greenhouse gas emissions (GHG) • • Human activities (“anthropogenic”) Source: IPCC AR5 report

6 Climate Change • Change compared with what? • Relative to a given historical period • 2081-2100 vs. 1986-2005 Source: IPCC AR5 report

7 Projected Changes Source: IPCC AR5 report

8 Climate and forest insects • Individual Growth and development • • Flight • Diapause Population • • Population density • Voltinism • Synchronous emergence

9 Climate and Eruptive Forest Insects Climate Outbreak Temperature Synchrony Natural Herbivory Insects Trees enemies Defense

10 Impacts of climate change on forest insects Source: IPCC AR5 report Changes in outbreak potential and range shift   Over-wintering survival  Increased voltinism  Stressed host trees

11 Climate and Forest Pathogens www.apsnet.org • Germination and infection Growth and reproduction • Dissemination •

12 Impacts of climate change on forest diseases Changes in distribution, intensity, and severity  Impacts vary by pathogen and climatic condition  • Warmer/Drier: Increased impact by Armillaria root disease Warmer/Wetter: Increased impact by Phytophthora ramorum •

13 Outline 1. Climate change 2. Climate vs. Forest pest distributions Empirical modelling • • Dendroctonus ponderosae • Ceratocystis polonica • Trends • Dendroctonus ponderosae 3. Summary

14 Climate vs. Forest pest distributions  Empirical modelling  Observing trends y = f (x)

15 Empirical models  Understand insect or disease occurrences as a function of environmental factors  Quantify the contributions of factors driving pest distributions and their spread  Make predictions over time and/or space  Study potential range distributions under climate change for native and invasive alien pest species

16 How are the models developed? 1. Species occurrence data 2. Environmental data 3. Modelling Framework http://www.jeffersoncountywi.gov/

17 How are the models developed? 1. Species occurrence data  Types of data 1. Point 2. Area 3. Grid

18 How are the models developed? 2. Environmental data  Variable types  Climate  Topography  Habitat https://asemedtraining.files.wordpress.com/2013/02/gis-layer-1.png

19 How are the models developed? 3. Modelling Framework  Statistical models  Climatic profiles  Machine learning

20 Conceptual Diagram Species data Environmental data Modelling Framework Predictions Time Space Climate change impacts Invasive species risk

21 Modelling Framework  Statistical Models  Climatic profiles Photo: Donald Owen, CAL FIRE, Bugwood.org Changes in mountain pine beetle outbreak risk under simulated climate change conditions

22 Mountain Pine Beetle, Dendroctonus ponderosae Photo: Brytten Steed, USDA-FS, Bugwood.org

23 Life Cycle of Mountain Pine Beetle Aug-Sept. July-August May-June July-August Photo credits: Egg: Brytten Steed, USDA-FS, Bugwood.org; Larva: Scott Tunnock, USDA-FS, Bugwood.org; pupa: USDA-FS - Ogden Archive, Bugwood.org; Flying adult: Dion Manastyrski, Ministry of Forests, Southern Interior Forest Region

24 Epidemiology of mountain pine beetle Photos: DPW Huber

25 Photos: DPW Huber

26 Fungal associates of the mountain pine beetle • Grosmannia clavigera and Ophiostoma montium • Carried in mycangia or on beetle exoskeleton • Help the insect colonize and kill a host tree http://genomealberta.ca

27 Mountain pine beetle outbreak history 12 10 Area affected (Mha) 8 6 4 2 0 1910 1930 1950 1970 1990 2010 Year Alberta British Columbia

28 Mountain pine beetle outbreak progression

29 Jack pine Eastern white pine Red pine

30 Climate change impacts • Used aerial survey data sets of mountain pine beetle infestations • Associated climate and elevation information with presence or absence of infestations Modelled outbreak occurrence under simulated climate change scenarios •

31 Climate change impacts Model Degree Spatial Temporal Temperature days infestations infestations Summer Temperature Winter Temperature Temperature Cold Snaps Drops Extreme min. thresholds Sambaraju et al. Ecography (2012)

32 Results: Changes in outbreak risk by latitude under a 1ºC temperature increase scenario 20 Risk # grid cells with altered outbreak risk 10 0 10 Risk 20 0 1 2 3 4 5 6 7 8 5 5 5 5 5 5 5 5 5 - - - - - - - - - 9 0 1 2 3 4 5 6 7 4 5 5 5 5 5 5 5 5 Latitude (°N)

33 Results: Changes in outbreak risk by latitude under a 2ºC temperature increase scenario 20 # grid cells with altered outbreak risk Risk 10 0 10 Risk 20 0 1 2 3 4 5 6 7 8 5 5 5 5 5 5 5 5 5 - - - - - - - - - 9 0 1 2 3 4 5 6 7 4 5 5 5 5 5 5 5 5 Latitude (°N)

34 Results: Changes in outbreak risk by latitude under a 4ºC temperature increase scenario 20 Risk # grid cells with altered outbreak risk 10 0 10 Risk 20 49-50 50-51 51-52 52-53 53-54 54-55 55-56 56-57 57-58 Latitude (°N)

35 Climate change impacts - Main conclusions • Probability of outbreaks may increase northward under high temperature regimes in future • Range shifts toward northern latitudes and higher elevations can be expected

36 Empirical Modelling Species data Environmental data Modelling Framework Predictions Time Space Climate Change impacts Invasive species risk

37 Modelling Framework  Statistical Models  Climatic profiles Climatic suitability for the exotic fungal pathogen, Ceratocystis polonica , in Canada

38 European spruce bark beetle, Ips typographus • Major insect infesting spruce in Eurasia • Epidemic populations kill healthy trees • Interceptions at ports of entry in Canada and USA Credit: Daniel Adam, Office National des Forêts, Bugwood.org

39 Fungal associates of the European spruce bark beetle • Important associates include Ceratocystis polonica and several species of Ophiostoma ( O. penicillatum, O. bicolor , O. piceae ) • C. polonica is the most aggressive among the fungal associates • Risk posed by C. polonica to Canada’s forests: • It is the most pathogenic associate of I. typographus • I. typographus can survive well on North American spruces (Økland et al. 2011) • Climate change could help the insect to establish in Canada

40 Distribution of C. polonica in Europe

41 Bioclimatic tolerance limits Climatic parameters Temperature Annual Temperature (Min, Max, Mean) Mean Quarterly Temperature (Wettest, Driest, Warmest, Coldest) Mean Monthly Temperature (Warmest, Coldest) Precipitation Annual Precipitation Quarterly Precipitation (Wettest, Driest, Warmest, Coldest) Monthly Precipitation (Wettest, Driest) Moisture Stress Annual Aridity Index Quarterly Aridity Index (Wettest, Driest, Warmest, Coldest)

42 Sample bioclimatic profile Parameter Minimum 10% 90% Maximum Annual Precipitation (cm) 37.1 73.3 139.7 184.8 Warmest quarter T mean (°C) 13.1 13.7 20.0 24.5 Warmest quarter aridity index (cm) 0 0 18.6 22.2 Warmest quarter precipitation (cm) 15.0 16.5 45.7 68.2 Driest quarter T mean (°C) -14.8 -6.2 14.9 18.2 Driest quarter aridity index (cm) 0 0 13.1 30.2 Coldest quarter T mean (°C) -14.8 -7.8 2.4 4.5 • Extrapolate bioclimatic profile to locations in Canada

43 Climate vs. Pest species distributions  Model framework  Observing trends y = f (x)

44 Observing Trends • Used MPB aerial survey data from British Columbia during 1965-1996 • Analyzed pre-outbreak populations • Calculated average deviations (3-yr) for aridity and temperature from the ‘normal’ • Averaged the climatic deviations from the ‘normal’ across all locations per year

45 Aridity regimes vs. Latitudinal range shifts 1,4 57 1,3 56 Above normal 1,2 Latitude Aridity 55 Aridity Ratio Latitude 1,1 ~ 300 km 54 1 53 Below 0,9 normal 0,8 52 1965 1970 1975 1990 1995 Year

46 Temperature regimes vs. Latitudinal range shifts 2 57 Average temperature Latitude Change in temperature ( ° C) Above 1 56 normal 0 55 Latitude -1 54 + 2.5°C -2 53 Below normal -3 52 1965 1970 1975 1990 1995 Year