1. How Scientists Study Climate Change A Rangeland Perspective Photo: Sam Cox

2. How Scientists Study Climate Change Reviewing our present state of knowledge –What we know (accepted by scientists) –Predictions; implications; uncertainty How we study the problem (techniques that scientist use, their strengths and limitations) –Observation –Manipulative experimentation –Modeling

3. WHAT WE KNOW: Atmospheric CO 2 concentrations measured accurately for many decades; they are steadily increasing. Charles David Keeling 1928-2005 2002 Nat’l Medal of Science Annual cycle due to photosynthesis and respiration of soils. Long term trend due to emission of fossil fuels

4. IPCC Working Group I Report, Chapter 2, 2007 WHAT WE KNOW: Ice core sampling & other techniques indicate rising CO 2 in Earth’s atmosphere is a relatively new phenomenon.

5. WHAT WE KNOW: A direct effect of rising CO 2 : Stimulation of plant growth. Nutrients, H 2 O CO 2 Food, Glorious Food! Any change in light, water, nutrients or carbon dioxide will alter plant growth.

6. WHAT WE KNOW: Global average surface temperature has increased 0.74 C (1.2 F) in the last hundred years. Rate of warming has doubled in the past 50 years. Predictions indicate future accelerated & extreme warming. IPCC 2007: WG1-AR4

7. IMPLICATIONS OF WHAT WE KNOW Warmer temperatures mean: Longer growing season Desiccation due to warming Altered hydrologic cycle atmosphere holds more water vapor intense rainfall events timing (altered seasonal precipitation; earlier loss of snow pack) some regions will experience more drought Photo: Sam Cox

8. How will climate change be expressed at local and regional scales? How will rangelands respond to increased occurrences of extreme events? How will rising CO 2, warmer temperature and altered pre- cipitation affect rangelands? How will rangelands & rangeland managers adapt to a more variable environment? Areas of Uncertainty weather, climate rangeland responses How will climate change be expressed at regional and local levels? Photos: Cox, Derner & SGS LTER

9. OBSERVATIONAL INFORMATION: Historical records & correspondences of early explorers & settlers. Caption from Barker et al., 1934 speaks of “ Coronado and his Band …wandering across … burning sands”, but the expeditions journal of 1541 recorded not deserts but grasslands. (Hart and Hart. 1997. Rangelands 19:4-11)

10. OBSERVATIONAL INFORMATION: Photographs can provide additional qualitative information Honey locust tree islands in Kansas Tallgrass Prairie. Present-day encroachment? Fire removal, climate change, CO 2 ? (photograph courtesy of Alan K. Knapp). Mesquite encroachment in SW over past two centuries (photograph courtesy of ARS Jornada Experimental Range photo gallery).

11. OBSERVATIONAL INFORMATION: Quantitative monitoring for management purposes may be especially useful for climate change Aerial photography & imaging software for quantifying range condition. High resolution infor- mation for assessing rangeland ecological services. Booth, Cox & Simonds

12. Observation Combined with Experimental Treatments Over Time Can Be Powerful Derner & Schuman. 2007. Jour. Soil & Water Cons. 62:77-85

13. 0-10 ka Bignell Loess 10-13 ka Brady Soil 13-23 ka Peoria Loess % C4 Vegetation Warmer/dry C4 grasses Cooler/wet C3 shrubs & grasses Kelly and Busacca, in Prep Plants leave geochemical fingerprints in soils !

14. Observational Information Information on ecosystem attributes, obtained in realistic environments, oftentimes of considerable time lengths Information is often complicated by other factors, like management, which have changed over time Interpretations often speculative Limited information on future environments, including multiple changes

15. Manipulative Research for Assessing Ecosystem Responses to CC Free Air CO 2 Enrichment in Mojave IR Warming on Tibetan Plateau Precipitation manipulation in Kansas tallgrass Mostly single factor experiments Run for two to several years Photos: Nowak, Wang & Knapp

16. Open Top Chamber CO 2 Enrichment Work on the Colorado Shortgrass Steppe: 1996-2001 USDA-ARS & Shortgrass Steppe LTER Doubling Ambient CO 2 : Increased NPP 44% Increased plant WUE Favored some plant spp. over others Forage N and forage quality declined CO 2 -production responses cool-season, C 3 grasses fringed sage, 40-fold

17. Prairie Heating and CO 2 Enrichment (PHACE) Cheyenne, Wyoming, USA (summer, 2008)

18. ACNAHNECN EHN ACI s ACI d PHACE EXPERIMENTAL TREATMENTS CO 2 A (present ambient, 380 ppm), E (elevated, 600 ppm) TEMP C (present temp), H (+ 1.5/3.0 C day/night) IRRIG I s (several seasonal water additions), N (non-irrigated) IRRIG I d (one or two annual water additions) 2 CO 2 by 2 TEMP factorial (5 reps each) 2 IRRIG Trts (5 reps each) Ambient CO 2 Ambient temp No irrigation Ambient CO 2 High temp No irrigation High CO 2 Ambient temp No irrigation High CO 2 High Temp No irrigation Ambient CO 2 Ambient temp Shallow irrigation Ambient CO 2 Ambient temp Deep irrigation

19. ACNAHNECNEHNACI s ACI d PHACE EXPERIMENTAL TREATMENTS CO 2 A (present ambient, 380 ppm), E (elevated, 600 ppm) TEMP C (present temp), H (+ 1.5/3.0 C day/night) IRRIG I s (several seasonal water additions), N (non-irrigated) IRRIG I d (one or two annual water additions) High CO 2 Ambient temp No irrigation Ambient CO 2 Ambient temp Shallow irrigation Does water replacement give the same response as elevated CO 2 ?

20. Prairie Heating and CO 2 Enrichment (PHACE) Experiment (Cheyenne, WY, USA) Direct Responses to GC Factors Indirect Effects of Water CO 2 ring Sentek SWC

21. Trace gas exchange Root dynamics Plant species abundances Canopy photosynthesis

22. Manipulative Experiments Can expose plants and plant communities to altered environmental conditions Can provide mechanistic information (NOT considered simulations of the future) Manipulations artificial, often with known and unknown artifacts Costly Few multiple GC experiments

23. Modeling Mathematical representations of reality –empirical (based on observation; practical) –theoretical (based on mechanisms) Useful for understanding how systems function Can fill in knowledge gaps Predictive tools

24. Epstein, Gill, Paruelo, Lauenroth, Jia and Burke. 2002. J. of Biogeography 29:875-888 Modeled Future Relative Abundances in Temperate Grasslands of North & South America. Based on: GCMs Relative Abundance Equations Based on observations & measurements obtained in the real world. Empirical relationships may not capture CO 2 response Plant Community Modeling

25. Summary Observation, manipulation, & modeling: useful tools for studying climate change and impacts on rangelands The complexities and uncertainties of climate change argue strongly for –utilizing all of these in our predictions –accepting that policy and management decision will always rely on a certain amount of uncertainty

26. Summary Science can help us understand & deal with that uncertainty –weather forecasting, monitoring and decision support systems can help us cope with an increasingly uncertain world –learning from other regions/countries where today we may find examples of our future climates (e.g., Australia in terms of variable weather)

27. THANKS FOR YOUR ATTENTION 2008 SUMMER HARVEST FIELD CREW 2008 SUMMER BIOMASS FIELD CREW