Deer ticks (Ixodes scapularis) are primary vectors of the bacteria that causes Lyme disease (Borrelia burgdorferi). With ever-changing climate and land use patterns, concerns have been raised about the potential for increasing deer tick populations.. Understanding tick population trajectories may thus inform both public health and ecosystem management.
Yet, a major challenge of incorporating typical field-based research into actionable information is that most biological studies are short term (i.e. 2-3 years). Trends observed may not be indicative of longer term patterns and could represent minor variation on a much larger temporal scale. Additionally, to study deer tick populations, researchers rely on several different methods including dragging and flagging, baited traps, and passive opportunistic surveys on different tick life stages - making it difficult to compare across studies.
We examined how study length, tick life stage, and sampling method influenced researchers’ understanding of deer tick population trajectories. We used a non-random resampling algorithm and a moving window approach on publicly available deer tick datasets with 9+ years of density or count data to re-analyze at all possible sampling year durations. This method allowed us to understand the sampling length required to detect consistent patterns and how frequently misleading trends are found.
Results/Conclusions
Using a systematic search protocol, we compiled publicly available, observational, long-term (9 or more years), US-based deer tick studies that met our study criteria. These studies generated 289 observations across 5 US states and 20+ years (studies ranged from 9 - 24 years long between 1995-2017). . We found that datasets reached stability (consistent patterns) after 6 or more years, and over half the datasets only reached stability in 10+ years. We also found that while there was no difference overall to stability by sampling method, datasets that used passive, opportunistic surveillance (e.g. ticks found on a person) varied much more widely in how long it took to converge on stable patterns compared to dragging field-sampling methods. Additionally, we found that while time to reach stability did vary slightly by deer tick life stage, studies that included multiple life stages exhibited much more variation.
Our findings indicate that short-term studies of deer ticks may give researchers misleading results when it comes to understanding long-term population patterns. Long-term field-biology studies have provided enormous insights for basic and applied ecological questions, and our research further supports their value and importance.