 This study compared the performance of various trend estimation methods when applied to long-term normalized difference vegetation index, NDDI, time series. The authors found that the best performing methods were those which removed the seasonality of the data and used annual aggregates. They also noted that these methods tended to underestimate the number of breaks in the data, which could lead to incorrect conclusions about the direction of change. Additionally, they found that the presence of large wildfires coincided with many of the breakpoints identified by their methods. This suggests that wildfire activity may play a role in the observed changes in vegetation productivity. This article was authored by Marcus Reichstein, Miguel de Mahetcha, Christopher S. Arnais, and others.