More than 100 years ago it was predicted that the distribution of first digits of real world observations would not be uniform, but instead follow a trend where measurements with lower first digit (1,2,…) occur more frequently than those with higher first digits (…,8,9). This result has long been known but regarded largely as a mathematical curiosity and received little attention in the natural sciences. Here we show that the first digit rule is likely to be a widespread phenomenon and may provide new ways to detect anomalous signals in data. We test 15 sets of modern observations drawn from the fields of physics, astronomy, geophysics, chemistry, engineering and mathematics, and show that Benford's law holds for them all. These include geophysical observables such as the length of time between geomagnetic reversals, depths of earthquakes, models of Earth's gravity, geomagnetic and seismic structure. In addition we find it also holds for other natural science observables such as the rotation frequencies of pulsars; green-house gas emissions, the masses of exoplanets as well as numbers of infectious diseases reported to the World Health Organization. The wide range of areas where it is manifested opens up new possibilities for exploitation. An illustration is given of how seismic energy from an earthquake can be detected from just the first digit distribution of displacement counts on a seismometer, i.e., without actually looking at the details of a seismogram at all. This led to the first ever detection of an earthquake using first digit information alone.