Climate variability and treeline dynamics in the Greater Yellowstone Ecosystem Anne M. Schrag
advertisement
Climate variability and treeline dynamics in the Greater Yellowstone Ecosystem Anne M. Schrag1, Andrew G. Bunn2, Lisa J. Graumlich1 1Big Sky Institute, Montana State University 2Huxley College of the Environment, Western Washington University Species Response to Climate Change Shifting geographical ranges Species-specific responses Evidence in paleo record How can we use the relationship between environmental variables and species distributions to understand past and future change? Alpine treeline ecotone Dynamic equilibrium Upper limit of conifer growth Lack of human influences Historical emphasis on temperature – New studies show influence of precip Integrating climate change & management When does risk of climate change effects justify mgt actions? How do you manage for climate change in natural areas that are not ‘managed’? Objectives Develop bioclimatic envelope models to establish relationship between current and future distribution of treeline species Determine the spatial and temporal effects of moisture availability on treeline species composition using historical data Bioclimatic envelope models Species presence/absence (FIA) Climate variables (DAYMET) Soil variables (CONUS-SOIL [STATSGO]) Random forest prediction method Input data Random subset of the data & random suite of predictor variables * Number of trees * Number of variables to try Calculate out-of-bag error rate Aggregate to one model Bioclimatic envelope models Three climate scenarios: – – – Increase temp by 4.5ºC Increase precip by 35% Increase temp & precip Mapped results across landscape Engelmann spruce Subalpine fir Whitebark pine 66.19% 66.55% 76.73% Current Subalpine fir Incr Precip Incr Temp Incr Both 42.56% 52.80% 14.13% 17.28% Current Engelmann spruce Incr Precip Incr Temp Incr Both 28.69% 30.66% 2.98% 5.02% Current Whitebark pine Incr Precip Incr Temp Incr Both 12.18% 13.02% 0.02% 0.02% Overall changes Increase tempÆdecrease in available habitat for all species Increase precipÆincrease in wet, midelevation habitat for all species Mid-elevationsÆreplacement of mixedconifer forest by spruce-fir complex (connectivity) Importance of predictor variables Subalpine fir Engelmann spruce Whitebark pine Spatial & historical variability 32 20x20m plots in four precipitation categories Tally mature and immature stems Core trees >10cm DBH Spatial influence of moisture 12 Precip Precip Precip Precip Avg stems/plot 10 Quartile Quartile Quartile Quartile 1 2 3 4 8 6 4 2 0 Subalpine ABLA fir Whitebark PIAL pine Engelmann PCENspruce Spatial influence of moisture Fir and spruceÆpositive correlation Whitebark pineÆnegative correlation – DAYMET (1980-1997) Fir: r=0.377 (p=0.03) Spruce: r=0.427 (p=0.01) Pine: r=-0.682 (p=<0.0001) – PRISM (1895-2004) Fir: r=0.251 (p=0.17) Spruce: r=0.420 (p=0.02) Pine: r=-0.619 (p=0.0001) Historical variability Overall, 42.94% of trees est. post-1895 – – – 45.24% fir 49.49% spruce 37.64% pine No apparent relationship between moisture availability and… – – – Number of ‘saplings’ (<10cm dbh & >0.5m tall) Number of ‘seedlings’ (<0.5m tall) Total number of stems per plot Management Implications Changes in spatial distribution coupled with moisture across landscape The Whitebark Story – ‘functionally extinct in a third of its range’ – multiple stressors – impacts to threatened species – focus on mixed-conifer, mid-elevation forests – couple blister rust, mtn pine beetle, land use, fire & climate models Courtesy of Riley McClelland A big thanks to… Big Sky Institute • Rick Lawrence • Aaron Jones • Greg Pederson • Todd Kipfer • Diane Eagleson Field & Lab Assistance • Jason Leppi • Ashley Lehman • Greg King • Sarah Stehn Greater Yellowstone I&M Network • Cathie Jean • Rob Bennetts • Elizabeth Crowe • Rob Daley
