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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. [ABSTRACT FROM AUTHOR]

Zöller et al. (Ethology, 2020) criticize our original publication (Wikelski et al., Ethology, 126(9), 2020, 931) for obvious reasons: we only observed the behavior of one group of farm animals before, during and after one earthquake series in one area of the world. It is clear that no earthquake predictions are possible, and should not be attempted, from this data set. However, what we show is that there is important information within this animal collective pertaining to potential future local forecasting of earthquakes when combined with traditional data sources. We maintain that combining Zöller et al.'s (2020) modeling tools with the adequate use of our data can stimulate novel ways of earthquake forecasting. Future studies should combine both approaches. [ABSTRACT FROM AUTHOR]

This article is a study of bicameral conflict resolution between the Council and the European Parliament in the European Union, which has established a bicameral conciliation process under the co-decision procedure. Scholars commonly agree that the European Parliament has gained power under the co-decision procedure, but the impact of the conciliation process on the power distribution between the Council and the European Parliament remains unclear. The scholarly debate suggests that the power of the institutional actors depends on their proximity to the status quo, the (im-)patience and the specific preference distribution of the institutional actors, although most analyses assume that the Commission plays an insignificant role. Using an ordered probit model, this study examines the power distribution between the two institutional actors, the factors for their bargaining success and the role of the Commission in the period between 1999 and 2002. The findings show that the European Parliament wins most conflicts, but that the Council is more successful in multi-dimensional disputes. The results confirm some theoretical claims made in the literature, such as the importance of the status quo location and of preference cohesiveness. However, they also reject a major assumption in the literature on the irrelevance of the Commission in the conciliation process, which we show to have an influential informational position for parliamentary success. [ABSTRACT FROM AUTHOR]