I’ve just been accepted to the Data to Knowledge Conference in Berkeley this May. I think this conference will address some of the key issues facing us in Big Data today across many different fields, and I hope to learn much that could be useful to ecology and evolution. Given the audience I look forward to being a source of questions rather than answers as I put on my biologist’s cap. Berkeley’s particular leadership in this area is probably evident in the millions of dollars they are receiving from the various initiatives coming out of today’s Big Data announcement. What better day to apply?
Many complex systems, from ecosystems to economies to governments, can undergo sudden and often catastrophic transitions between alternate stable states. Ecologists have recently begun to demonstrate the existence of certain early warning signals or leading indicators – patterns that suggest an ecosystem is approaching a critical transition such as the collapse of a population or eutrophication of a lake. Though these patterns are extremely subtle and consequently require large amounts of data to generate an adequate ratio of signal to noise, technology such as satellite imaging and microchip sensors have dramatically increased the data available. Will this recent data deluge help us detect critical transitions with enough time avert them?
I will briefly introduce recent advances in the field of early warning signals and discuss my work to transition this from a proof of principle to a quantifiable risk that can inform policy.