1. Observing Systems for Multiscale Processes: Connectivity across Scales, How to design observing systems, Sampling program

2. Daly Milliff Bisagni Bucklin Fiechter Holland Pierson Rykaczewski Turner Group Members

3. Past GLOBEC regions were chosen as areas with existing series of observations (e.g., MARMAP) to give context to the research – Ecological “hot spots” – Commercially important spp – Recognized zoopl as indicators, but not mechanistic understanding Directed effort towards retrospective analysis of existing obs datasets Retro, modeling and techno development before field program Embedded process studies in context of long-term observations Observations and modeling went forward together, physical and ecological observations on same scale Recognition that basin-scale climate variability influenced ecosystem processes on local/mesoscale

4. Present Current PRS groups have responsibility to consider obs systems and translate research results that will be useful w/in context of observing systems – Recommend sensor systems and sampling programs relevant to coupled physical- ecosystem models – Develop metrics for co-evaluating integrated measurement systems and models – What are sentinel measurements to make, indicators of climate change? GLOBEC has made contributions to development of emerging IOOS and OOI through research results and PI interaction – Not always recognized as GLOBEC contribution – “branding” need GLOBEC should continue to refine concepts of adaptive sampling to measure critical events (episodes) – Vs. CalCOFI static, regular grid – Refine error bars on abundance and rates estimates Refine mechanistic understanding to define lead-lag relationships between ecosystem change and climate variability – Will current hot spots remain persistent in a changing climate? GLOBEC is an approach, not just a program – Incorporated into new programs (Chilean, FUTURE, BASIN…) – Suggest “culminating” article in EOS (teaser for GLOBEC books)

5. Future (not FUTURE) GLOBEC should make recommendations for model development needs for obs systems Models necessary for dynamic interpolation and prediction Challenge in spanning scales (bacteria to whales; individual to populations; episodic events to long term climate scales;) Obs of model domain boundary variability will improve models Climatology not enough Can’t compare obs data with single model output – Ensemble approaches – Develop new methods for model-data comparisons (Spatial/temporal basis functions) Develop model comparison methods Intercompare observing regions to evaluate connectivity, teleconnections, covariability among regions Recommend measurements and rate processes to encourage development of sensing systems for fundamental ecological processes – E.g. genomic metabolic processes