|Aim The Hutchinsonian hypervolume is the conceptual foundation for many lines
of ecological and evolutionary inquiry, including functional morphology, comparative
biology, community ecology and niche theory. However, extant methods to
sample from hypervolumes or measure their geometry perform poorly on highdimensional
or holey datasets.
Innovation We first highlight the conceptual and computational issues that have
prevented a more direct approach to measuring hypervolumes. Next, we present a
new multivariate kernel density estimation method that resolves many of these
problems in an arbitrary number of dimensions.
Main conclusions We show that our method (implemented as the
‘hypervolume’ R package) can match several extant methods for hypervolume
geometry and species distribution modelling. Tools to quantify high-dimensional
ecological hypervolumes will enable a wide range of fundamental descriptive, inferential
and comparative questions to be addressed.|