AGE MODELS IN LARGE SCALE SYNTHESIS – DE NOVO OR STATUS QUO?

Large databases of paleoecological material (e.g., Neotoma Paleoecology Database) provide an opportunity to undertake analysis of climatic and ecological change at multiple scales. This kind of macrosystems approach (sensu Heffernan et al., 2014) is critical to understanding how changing climate can affect ecosystems at temporal scales beyond the limits of long-term ecological datasets, and at spatial scales of hundreds to thousands of kilometers.

There is significant interest in the use of these data for synthesis, but understanding temporal uncertainty at these time scales becomes a key piece in determining whether events are synchronous, time-transgressive, causative, or a response to changing climate or vegetation. Thus, the utility of paleoecological records relies on well dated material, and age models that can capture and report reliable estimates of uncertainty. However, in many cases analysts use published age models or reported ages without considering uncertainty. For example, Neotoma does not report age uncertainty for many cores, and many records use linearly interpolated age models (78% of all pollen cores in Neotoma) or are built with uncalibrated 14C ages (83% of all pollen cores in Neotoma), resulting in potentially flawed age estimates. Interpretations using these data may differ strongly from models that re-calibrate and rebuild age models from the available geochronological data.

Here we summarize the implications of using the status quo, report work to date (e.g., Goring et al., 2012; Blois et al., 2011) in improving age models in Neotoma, and look to ways forward for researchers interested in using these large paleoecological datasets using the Paleoecological Observatory Network (PalEON) as a case study.