Nonmetric multidimensional scaling (NMDS) is a powerful statistical tool which enables complex multivariate data sets to be visualized in a reduced number of dimensions. Users typically evaluate the fit of an NMDS ordination via ordination “stress” (i.e., data distortion) against a commonly accepted set of heuristic guidelines. However, these guidelines do not account for the mathematical relationship which links ordination stress to sample size. Consequently, researchers working with large data sets may unnecessarily present ordinations in an intractable number of dimensions, subdivide their data, or forego the use of NMDS entirely and lose the benefits of this highly flexible and useful technique. In order to overcome the limitations of these practices, we advocate for an alternative approach to the evaluation of NMDS ordination fit via the usage of permutation‐based ecological null models. We present the rationale for this approach from a theoretical basis, supported by a brief literature review, and an example usage of the methodology. Our literature review shows that NMDS analyses often far exceed the number of observations under which the original stress guidelines were formulated—with a significant increasing trend in recent decades. Adoption of a permutation‐based approach will consequently provide a more flexible and quantitative evaluation of NMDS fit and allow for the continued application of NMDS in an era of increasingly large datasets.

Diel vertical migration is widespread across diverse taxa in the world's lakes and seas, yet its biogeochemical consequences are still poorly understood. The biologically mediated vertical flux of material in the ocean (also known as the “biological pump”) is a matter of major interest and concern, as it is thought to play an important role in regulating ocean carbon storage, and by extension, the global carbon cycle. Recent studies spanning multiple trophic levels from fish to dinoflagellates have led us to a concept of coupled vertical migrations that we refer to as “cascading migrations”. That is, migrations that occur at one trophic level can affect the vertical migration of the next lower trophic level, and so on throughout the food web (e.g. carnivores affect the migrations of herbivores, which in turn affect the migrations of motile phytoplankton). Here we hypothesize that greater trophic complexity in the water column leads to enhanced cascading vertical migrations that in turn increase the vertical fluxes of materials and energy through the water column, both upwards and downwards. We recommend that a combination of observational, experimental and modeling approaches be employed to explicitly test this hypothesis.