|Title||Ecological challenges posed by climate uncertainty|
|Year of Publication||2015|
|Series Title||The Economic and Financial Risks of a Changing Climate; Insights from Leading Experts|
|ARIS Log Number||316918|
We’ve been collecting long-term data at many ecological and agricultural research sites across the United States and globally, in some cases for over 100 years. This means we have a lot of data, and we feel like we understand our ecosystems very well—up until the climate drivers start changing beyond the range of historic variability. These changes make us nervous because they cause the rules between the physical drivers and the biota to change—and, in particular, during extreme events, including heat waves, freezes, floods, and droughts. It’s very difficult for ecologists to deal with extreme events because we need long-term data to observe and understand events that rarely occur. Take something that occurs very infrequently, such as the Florida citrus freeze: How do we study that? How do we prepare for that? The other aspect of these events deals with space. A lot of ecological studies are small-plot studies, at a scale as small as a meter square in grasslands and up to a hectare in forests. You can imagine those plots don’t represent very much area, and we have to do replications in order to understand these problems really well. What we really need to know is how to extrapolate these small-plot dynamics spatially so we can predict how large landscapes will respond to climate change. These large landscapes are difficult, if not impossible, to replicate. Propagating events—such as wildfires or species invasions—come into play when we put space and time together in what we call cross-scale interactions. These land–atmosphere interactions that start small and propagate to have large impacts are the really big uncertainties that may become more frequent in the future as both the climate and land-use drivers change. Although our long-term data are invaluable at providing context for the present and future, the changing rules will make predictions of the future challenging without a strong understanding of the underlying mechanisms and their interactions that are driving those changes.