Predicting ecosystem resilience is a challenge, especially as climate change alters disturbance regimes and conditions for recovery. Recent research has highlighted the importance of spatially-explicit disturbance and resilience processes to long-term ecosystem dynamics. “Neoecological” approaches characterize resilience mechanisms at relatively fine spatio-temporal resolutions, but results are difficult to extrapolate across broad temporal scales or climatic ranges. Paleoecological methodologies can consider the effects of climates that differ from today. However, they are often limited to coarse-grained spatio-temporal resolutions.

In this synthesis, we describe implicit and explicit examples of studies that incorporate both neo- and paleoecological approaches. We propose ways to build on the strengths of both approaches in an explicit and proactive fashion.

Linking the two approaches is a powerful way to surpass their respective limitations. Aligning spatial scales is critical: Paleoecological sampling design should incorporate knowledge of the spatial characteristics of the disturbance process, and neoecological studies benefit from a longer-term context to their conclusions. In some cases, modeling can incorporate non-spatial data from paleoecological records or emerging spatial paleo-data networks with mechanistic disturbance/recovery processes that operate at fine spatiotemporal scales.

Linking these two complementary approaches is a powerful way to build a complete understanding of ecosystem disturbance and resilience.