Potential short-term earthquake forecasting by farm animal monitoring

Whether changes in animal behavior allow for short-term earthquake
predictions has been debated for a long time. Before, during and after the
2016/2017 earthquake sequence in Italy, we deployed bio-logging tags to
continuously observe the activity of farm animals (cows, dogs, sheep)
close to the epicenter of the devastating magnitude M6.6 Norcia earthquake
(Oct-Nov 2016) and over a subsequent longer observation period (Jan-Apr
2017). Relating 5304 (in 2016) and 12948 (in 2017) earthquakes with a wide
magnitude range (0.4 ≤ M ≤ 6.6) to continuously measured animal activity,
we detected how the animals collectively reacted to earthquakes. We also
found consistent anticipatory activity prior to earthquakes during times
when the animals were in a building (stable), but not during their time on
a pasture. We detected these anticipatory patterns not only in periods
with high, but also in periods of low seismic activity. Earthquake
anticipation times (1-20hrs) are negatively correlated with the distance
between the farm and earthquake hypocenters. Our study suggests that
continuous bio-logging of animal collectives has the potential to provide
statistically reliable patterns of pre-seismic activity that could yield
valuable insights for short-term earthquake forecasting. Based on a-priori
model parameters we provide empirical threshold values for pre-seismic
animal activities to be used in real-time observation stations.