|Title||How long do population level field experiments need to be? Utilising data from the 40-year-old LTER network|
|Publication Type||Journal Article|
|Year of Publication||2021|
|Authors||Cusser, S, Helms, J, Bahlai, CA, Haddad, NM|
|Pagination||1103 - 1111|
|Keywords||Data mining, isothermality, Long-term, LTER-HBR, moving window, Population dynamics, time series, trajectory|
We utilise the wealth of data accessible through the 40-year-old Long-Term Ecological Research (LTER) network to ask if aspects of the study environment or taxa alter the duration of research necessary to detect consistent results. To do this, we use a moving-window algorithm. We limit our analysis to long-term (> 10 year) press experiments recording organismal abundance. We find that studies conducted in dynamic abiotic environments need longer periods of study to reach consistent results, as compared to those conducted in more moderated environments. Studies of plants were more often characterised by spurious results than those on animals. Nearly half of the studies we investigated required 10 years or longer to become consistent, where all significant trends agreed in direction, and four studies (of 100) required longer than 20 years. Here, we champion the importance of long-term data and bolster the value of multi-decadal experiments in understanding, explaining and predicting long-term trends.