Uniting Experiments and Big Data to advance ecology and conservation

The use of ‘big data’ is increasingly championed as a scientific framework to help solve our global conservation crisis. Yet experiments are also advocated as essential for identifying mechanisms and interventions needed to solve this crisis.Big data can provide the scaffolding for documenting patterns across scales, whereas experiments can inform novel situations and provide the means for conservation actions.The complementarity of these frameworks provides untapped opportunities for leveraging the strengths of both frameworks through an integrative process.We outline an integrated framework that can address a range of conservation problems, including forecasting, ecological novelty, scaling, and generalization of conservation actions.