Logic of experiments in ecology: is pseudoreplication a pseudoissue?

Abstract

Hurlbert divides experimental ecologist into ‘those who do not see any need for dispersion (of replicated treatments and controls), and those who do recognize its importance and take whatever measures are necessary to achieve a good dose of it’. Experimental ecologists could also be divided into those who do not see any problems with sacrificing spatial and temporal scales in order to obtain replication, and those who understand that appropriate scale must always have priority over replication. If an experiment is conducted in a spatial or temporal scale, where the predictions of contesting hypotheses are convergent or ambiguous, no amount of technical impeccability can make the work instructive. Conversely, replication can always be obtained afterwards, by conducting more experiments with basically similar design in different areas and by using meta‐analysis. This approach even reduces the sampling bias obtained if resources are allocated to a small number of well‐replicated experiments. For a strict advocate of the hypothetico‐deductive method, replication is unnecessary even as a matter of principle, unless the predicted response is so weak that random background noise is a plausible excuse for a discrepancy between predictions and results. By definition, a prediction is an ‘all‐statement’, referring to all systems within a well‐defined category. What applies to all must apply to any. Hence, choosing two systems and assigning them randomly to a treatment and a control is normally an adequate design for a deductive experiment. The strength of such experiments depends on the firmness of the predictions and their a priori probability of corroboration. Replication is but one of many ways of reducing this probability. Whether the experiment is replicated or not, inferential statistics should always be used, to enable the reader to judge how well the apparent patterns in samples reflect real patterns in statistical populations. The concept ‘pseudoreplication’ amounts to entirely unwarranted stigmatization of a reasonable way to test predictions referring to large‐scale systems.

Effect of nitrogen fertilizer on nitrogen pools and soil communities under grazed pastures

“…Although true replication is often not feasible for studies performed at large spatial scales such as this, it has been argued that statistical analysis among systems for which replication is not tractable may still be legitimate provided sufficient caution is applied (see Carpenter 1989;Oksanen 2001). As such, we maintain that major differences between LF and HF fields for our response variables should serve as an authentic measure of the effects of soil fertility long term, because climatic conditions, soil, slope and aspect are effectively the same at both fields.…”

Long-term dynamics of aboveground fungal communities in a subalpine Norway spruce forest under elevated nitrogen input

“…Although these subplots should not be considered as true replicates because of the clumped segregation design (Hurlbert 1984; but see Oksanen 2001Oksanen , 2004, they allow testing the impact of spatial heterogeneity on the community response to treatment inside each experimental plot. Permutation tests with 1,000 permutations, stratified by year, were performed for every canonical axis and a PRC was plotted for each significant axis.…”

Ectomycorrhizal communities in a Tuber aestivum Vittad. orchard in Poland

“…testable only within a limited spatial scale. Unreplicated treatments were the only option for our study [24]. We controlled this problem by using randomized techniques for taxa richness data [25], as recommended and used elsewhere [26][27][28].…”