Long-term time series are necessary to better understand population dynamics, assess species’ conservation status, and make management decisions. However, population data are often expensive, requiring a lot of time and resources. What is the minimum population time series length required to detect significant trends in abundance? I first present an overview of the theory and past work that has tried to address this question. As a test of these approaches, I then examine 822 populations of vertebrate species. I show that 72% of time series required at least 10 years of continuous monitoring in order to achieve a high level of statistical power. However, the large variability between populations casts doubt on commonly used simple rules of thumb, such as those employed by the IUCN Red List. I argue that statistical power needs to be considered more often in monitoring programs. Short time series are likely underpowered and potentially misleading.

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