Abstract
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, and 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 5,304 (in 2016) and 12,948 (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 (1-20 hr) 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.