Sampling frequency, duration and the Southern Oscillation influence the ability of long-term studies to detect sudden change.

Ecologists have long acknowledged the importance of context dependency related to position along spatial gradients. It is also acknowledged that broad-scale climate patterns can directly and indirectly alter population dynamics. What is not often addressed is whether climate patterns such as the Southern Oscillation interact with population-level temporal patterns and affect the ability of time-series data, such as long-term state of the environment monitoring programmes, to detect change. Monitoring design criteria generally focus on number of data points, sampling frequency and duration, often derived from previous information on species seasonal and multi-year temporal patterns. Our study questioned whether the timing of any changes relative to Southern Oscillation, interacting with species populations dynamics, would also be important. We imposed a series of simulated reductions on macrofaunal abundance data collected regularly over 29 years from two sites, using species selected for observed differences in temporal dynamics. We hypothesized that (1) high within-year sampling frequency would increase detection ability for species with repeatable seasonality cycles and (2) timing of the reduction in abundance relative to the Southern Oscillation was only likely to affect detection ability for long-lived species with multi-year cyclic patterns in abundance. However, regardless of species population dynamics, we found both within-year sampling frequency and the timing of the imposed reduction relative to the Southern Oscillation Index affected detection ability. The latter result, while apparently demonstrating a confounding influence on monitoring, offers the opportunity to improve our ability to detect and interpret analyses of monitoring data, and thus our ability to make recommendations to managers.