1. USA-NPN 2006 Integrating Phenological Measurements into Climate Monitoring

2. USA-NPN 2006 Definition of Phenology u Phenology which is derived from the Greek word phaino meaning to show or to appear, is the study of periodic plant and animal life cycle events that are influenced by environmental changes, especially seasonal variations in temperature and precipitation driven by weather and climate. Thus, timings of phenological events are ideal indicators of global change impacts. u Seasonality is a related term, referring to similar non- biological events, such as timing of the fall formation and spring break-up of ice on fresh water lakes.

3. USA-NPN 2006 Examples of Phenology u Sprouting, leafing, and flowering of plants in spring u Leaf color change in autumn u Bird migration and nesting u Insect hatches u Animal emergence from hibernation

4. USA-NPN 2006 Lilac First Leaf

5. USA-NPN 2006 Lilac First Bloom

6. USA-NPN 2006 History of Phenology u Ancient and traditional uses related to agriculture, due to the connection of changes in the local environment to plant development. u Specific events can serve as “indicators” to guide other activities. This can be useful for garden planting in the spring, especially for early season crops, or if some early planting risk is needed to ensure success.

7. USA-NPN 2006 New Uses of Phenology u Global Change Science—phenological observations serve as an independent measure of the effect of climate change on biological organisms. u Ecosystem linkages—phenological observations at different levels of the food chain (plant growth, insect hatching, bird feeding/nesting) can shed light on “ripple effects” of climate change.

8. USA-NPN 2006 Critical Research Areas u Atmosphere-Biosphere Interactions u Long-term Organism response to Climate Change u Global Phenology Databases for monitoring and management

9. USA-NPN 2006 Carbon Assimilation CO 2 CH 4 N 2 O VOCs Dust Heat Moisture Momentum Climate Temperature, Precipitation, Radiation, Humidity, Wind Chemistry CO 2, CH 4, N 2 O ozone, aerosols Microclimate Canopy Physiology Species Composition Ecosystem Structure Nutrient Availability Water Disturbance Fires Hurricanes Ice Storms Windthrows Evaporation Transpiration Snow Melt Infiltration Runoff GPP, Plant & Microbial Respiration Nutrient Availability Ecosystems Species Composition Ecosystem Structure Watersheds Surface Water Subsurface Water Geomorphology Biogeophysics Energy Water Aero- dynamics Biogeochemistry Mineralization Decomposition Hydrology Soil Water Snow Inter- cepted Water Phenology Bud Break Leaf Senescence Hydrologic Cycle Vegetation Dynamics Minutes-To-Hours Days-To-Weeks Years-To-Centuries Phenology is an essential component of the biosphere Bonan (2002) Ecological Climatology: Concepts and Applications. Cambridge University Press

10. USA-NPN 2006 Phenology modulates terrestrial carbon cycles at multiple temporal & spatial scales Global Change Influences & is Influenced by Phenology Amplification of seasonal cycle

11. USA-NPN 2006 Global Phenological Monitoring Issues: Few Networks, Multiple Standards, and Little Coordination u Europe u Asia u North America u Southern Hemisphere u Role of ISB Phenology Commission

12. USA-NPN 2006

14. Jill Attenborough, Woodland Trust http://www.phenology.org.uk 157,000 observations from citizens In the UK in spring 2005 alone!

15. USA-NPN 2006 Elisabeth Beaubien Plantwatch National Coordinator University of Alberta, Edmonton www.naturewatch.ca

16. USA-NPN 2006 Example Benefits of Phenological Research/Data

17. USA-NPN 2006 Example Phenological Applications (emphasizing advantages of co-location/coordination with climate data)

18. USA-NPN 2006 Integrated Approach (to Data Collection) u Satellite Observations (MODIS-NDVI/EVI in USA) u Indicator Species Phenology u Native Species Phenology

19. USA-NPN 2006 Cloned lilac first leaf and first bloom dates at a single station in Vermont

20. USA-NPN 2006 Spring indices based on first leaf date for lilacs Schwartz and Reiter 2000 International. J. Climatology Syringa vulgaris (common lilac) Syringa chinensis (cloned lilac)

21. USA-NPN 2006 Spring Index based on Simulated First Leaf Date: Slope from 1961-2000 Spring Index based on Damage Index Value (First Leaf – Last Frost) Schwartz et al. 2006 Global Change Biology

22. USA-NPN 2006 Integrated Species Indices (ISI) southwestern Wisconsin

23. USA-NPN 2006 Diurnal Range Change with Lilac First Leaf Source: Schwartz 1996, Figure 3

24. USA-NPN 2006 Comparative Net Ecosystem Exchange

25. USA-NPN 2006 Spring Phenology Campaign 2006 u Spatially: 3/7 cyclic sampling; 25m unit distance; 300m×600m Area; 216 trees

26. USA-NPN 2006 Start-of-Season Comparisons

27. USA-NPN 2006 Hu, Q., Weiss, A., Feng, S., & Baenziger, P.S. (2006) Early winter wheat heading dates and warmer springs in the U.S. Great Plains. Agricultural and Forest Meteorology 135:284. Heading date: when head (spike) on 50% of the Kharkof cultivar emerges from the flag leaf. 1946

28. USA-NPN 2006 Phenology can help in detecting/anticipating climate change effects on the synchrony between organisms Plants and pollinators Natural enemies of insect pests

29. USA-NPN 2006 Forest wildfire frequency for early, mid and late tercile timing of spring since 1970. Correlation between large (> 400 ha) forest wildfire frequency & streamflow center timing. Fire Vulnerability associated with earlier spring onset. Vulnerability = % change moisture deficit with delayed spring onset, scaled by fraction of forest area Changes in Wildfire and the Timing of Spring in Western US Forests A.L. Westerling, H.G. Hidalgo, D.R. Cayan, T.W. Swetnam. Science (in press)

30. USA-NPN 2006 Vision of a USA National Phenology Network (NPN) u a continental-scale network observing regionally appropriate native plant species, cloned indicator plants (lilac +?), and selected agricultural crops u designed to complement remote sensing observations u data collected will be freely available to the research community and general public

31. USA-NPN 2006 PREAMBLE: Phenology is a far-reaching component of environmental science but is poorly understood. Critical questions include how environmental factors affect the phenology of different organisms, and how those factors vary in importance on different spatial and temporal scales. We need to know how phenology affects the abundance and diversity of organisms, their function and interactions in the environment, especially their effects on fluxes in water, energy, and chemical elements at various scales. With sufficient observations and understanding, phenology can be used as a predictor for other processes and variables of importance at local to global scales, and could drive a variety of ecological forecast models with both scientific and practical applications. USA-NPN Implementation Team 4/16/06

32. USA-NPN 2006 The predictive potential of phenological phenomena requires a new data resource, a national network of integrated phenological observations and the tools to analyze them at multiple scales. This network is essential to evaluate ongoing environmental changes. It can now capitalize on integration with other observation networks and remote sensing products, emerging technologies and data management capabilities, myriad educational opportunities, and a new readiness of the public to participate in investigations of nature on a national scale. USA-NPN Implementation Team 4/16/06

33. USA-NPN 2006 IntensiveSites Spatially Extensive Science Networks Remote Sensing and Synoptic (wall-to-wall) Data Decreasing Spatial Coverage Increasing Process Knowledge Data Quality # of Measurements USA-NPN Monitoring Framework Spatially Extensive Volunteer & Education Networks AmeriFlux, AgriFlux NSF LTER, NEON USGS WEBB USDA FS Exp. F & R NWS Coop NPS Inv. & Mon. USDA FIA State Ag. Exp. Sta. GLOBE Garden clubs Nat. Plant Soc. Campuses NASA USGS NOAA

34. USA-NPN 2006 Colocation with NWS Cooperative Observer Program (COOP) Tier 2: Example of Spatially Extensive Science Network

35. USA-NPN 2006 Tier 3: Example Of Volunteer & Education Networks

36. USA-NPN 2006 NPN-Tier 4: REMOTE SENSING can fill gaps between ground observations to produce a continuous surface of phenology estimates at the continental scale Start of season End of season Duration of season Peak season Seasonally integrated vegetation index Mandan, ND 19992000 Days offset n = 13 x = 2.23 std = 8.21 -10+5 Satellite SOS vs. GPP estimates (USDA-AgriFlux) Land surface phenology metrics, based on time-series Vegetation Index

37. USA-NPN 2006 http://www.uwm.edu/Dept/Geography/npn/

38. USA-NPN 2006 Milestones for USA-NPN 8/24-25/20051 st NPN Planning Workshop, Tucson funded by NSF, USGS, NPS, FS, & EPA 3/22-24/2006NPN Implementation Team meeting 6/12/2006Presentation USGS Exec. Leadership Team 8/15/2006USGS Bureau Planning Council approves $275K/yr for Natl. Coordinating Office 9/1/2006Univ. of AZ offers free space + Asst. Dir. 9/8/2006USGS approves plan to locate Natl. Office at Univ. of Arizona 10/1/2006USGS advertises Exec. Direction position 10/9-13/20062 nd NPN Planning Workshop, Milwaukee funded by NSF, USGS, FWS & NASA Fall/2006NSF RCN grant $500K/5 yrs hopefully funded 1/01/2007National Coordinating Office staffed and located in Tucson Spring 2007First set of observations nationwide

39. USA-NPN 2006 Global Phenological Monitoring: Implementation Challenges u Development of Protocols —in good shape thanks to BBCH standardization u Species selection/coordination —careful study and implementation using a nested approach u Data sharing agreements —non-trivial issue u Site Colocation and Integration Issues —being addressed by COST 725 action in Europe, different challenges in other regions

40. USA-NPN 2006 Recommendations u Draw from NPN and EPN/COST experience as templates for starting phenology networks in other places u Consider funding a study of how to best establish phenology networks, accounting for existing environmental networks and potential for volunteer observers (best by country or continent?) u First step could be promotion of phenological observations by national weather networks