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OBSERVING LIFE IN A TIME OF CHANGE:

OBSERVING LIFE IN A TIME OF CHANGE:. DAVE SCHIMEL | NEON, INC. Observing ecological change:. Anticipating the future using space for time substitution (which assumes quasi-equilibrium conditions) is compromised by today ’ s high rates of change.

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OBSERVING LIFE IN A TIME OF CHANGE:

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  1. OBSERVING LIFE IN A TIME OF CHANGE: DAVE SCHIMEL | NEON, INC.

  2. Observing ecological change: • Anticipating the future using space for time substitution (which assumes quasi-equilibrium conditions) is compromised by today’s high rates of change. • As a result, spatial data collected now and in the past contains more information than data collected in the future. • Context matters: the outcome of natural variability and experiments depends on the state of the system. • Connectivity matters: transport and mobility of matter, energy and organisms is of growing importance.

  3. Change is pervasiveClimate

  4. Land use

  5. Invasive species Tamarisk (Salt Cedar), introduced 1900 Cheatgrass (Bromus tectorum) introduced 1850

  6. A paleo-perspective on recent ecological change Williams et al 2007

  7. Niche estimation in the midst of change

  8. Successional dynamics, biogeochemistry and carbon fluxes Productivity Ocean Physics Nutrients Carbon Storage Species Composition

  9. Physical – Biological variability in the oceans: BATS From long term records to complex interpretation and analysis using models Gruber, Keeling and Gates, 2002

  10. Changes to the chemical climate:

  11. Coupling of terrestrial, aquatic and marine ecosystems at the continental scale by the Nitrogen cycle Can networks of Field and Ag Experiment Stations and Marine Labs contribute to solving this type of problem? Connectivity:

  12. Observed variability of fluxes Observing change directly-long time series

  13. Analysis of controls The importance of temporal embedded studies: what would any three years have suggested*? Warm springs accelerate growth but also evaporation, consistent with information from spatial flux patterns and atmospheric CO2 trends • *40% chance of being wrong

  14. Observing ecological change: • Space for time is increasingly compromised by high rates of change: thus, long time series grow in value with time. • Spatial data collected now and in the past contains more information than data collected in the future: availablelegacy data is an essential foundation for future models and forecasts. • Connectivity matters: there are limitations to isolated place-based research: linking networks of time series to achieve regional and continental scales is crucial. • Context matters: temporally embedded studies are important for understanding change: embedding process studies within well-documented sites is essential.

  15. Continental-scale ecology versus landscape-scale case studies(Frontiers, Oct 2011) However, we believe there is more to this trend than that described by Schimel. Lindenmayer and Likens (2011) recently pointed out a similar trend, but were much more critical of the phenomenon. A focus on modeling and mathematics, for example, might entail the loss of a “place-based culture” in ecology (Joern Fischer, Jan Hanspach, and Tibor Hartel) We live in a global village, and in an increasingly interconnected world. Great ecologists have long known this, and great ecology has been conducted at the continental scale for decades.… Local-scale ecology is in no danger. Making measurements at or close to the scale of organisms is natural and necessary, and many important processes occur in that domain, while field stations remain a vibrant part of ecological training, research, and culture. (me)

  16. Continental-Scale Ecologyor, confessions of a serial field station (aka continental-scale) scientist CPER Schimel, D.S., W.J. Parton, F.J. Adamsen, R.G. Woodmansee, R.L. Senft and M. A. Stillwell. 1986. The role of cattle in the volatile loss of nitrogen from a shortgrass steppe. Biogeochemistry 2:3 9-52. HJ Andrews Strickland, T.C., P. Sollins, N. Rudd, and D.S. Schimel. 1992. Rapid stabilization and mobilization of 15N in forest and range soils. Soil Biology & Biochemistry 24:849-855. Konza Prairie Davis, F.W., D.S. Schimel, M.A. Friedl, J.C. Michaelsen, T.G.F. Kittel, R. Dubayah and J. Dozier. 1992. Covariance of biophysical data with digital topographic and land use maps over the FIFE site. Journal of Geophysical Research 97:19,009-19,021. La Copita (TAMU) Asner, G.P., C.A. Wessman, and D.S. Schimel. 1998. Heterogeneity of savanna canopy structure and function from imaging spectrometry and inverse modeling. Ecological Applications 8:1022-1036. La Selva Reiners, W. A., S. Liu, K. G. Gerow, M. Keller, and D. S. Schimel (2002), Historical and future land use effects on N2O and NO emissions using an ensemble modeling approach: Costa Rica's Caribbean lowlands as an example, Global Biogeochem. Cycles, 16(4), 1068-1086. Harvard Forest Braswell, Bobby H., William J. Sacks, Ernst Linder, and David S. Schimel. 2005. Estimating diurnal to annual ecosystem parameters by synthesis of a carbon flux model with eddy covariance net ecosystem exchange observations. Global Change Biology: 2, pp 197–367 Niwot Ridge Sacks, W. J., Schimel, D. S., Monson, R. K. and Braswel, B. H. (2006), Model-data synthesis of diurnal and seasonal CO2 fluxes at Niwot Ridge, Colorado. Global Change Biology, 12: 240–259

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