As we enter the era of data science (Lortie 2018), quantitative analysis methodologies are proliferating rapidly, leaving ecologists with the task of choosing among many alternatives.
The use of structural equation modeling (SEM) by ecologists has increased in recent years, prompting us to ask users a number of questions about their experience with the methodology. Responses indicate an enthusiastic endorsement of SEM. Two major elements of respondent’s experiences seem to contribute to their positive response, (1) a sense that they are obtaining more accurate explanatory understanding through the use of SEM and (2) excitement generated by the discovery of novel insights into their systems. We elaborate here on the detection of indirect effects, offsetting effects, and suppressed effects, and demonstrate how discovering these effects can advance ecology.