A new approach for detecting phenological change using Time of Emergence (ToE) methodology

Many species are responding to environmental change by shifting the timings of phenological events such as migration or reproduction. These shifts are typically reported as rates of change, which do not indicate when such shifts transcend their original states, nor consider whether species experience novel environmental conditions or phenological mismatch with other species at their phenological events.
We present a new, generalizable approach to detect and contextualize shifts in phenological data regardless of taxonomic group or location by applying statistical and empirical Time of Emergence (ToE) metrics derived from climate science.
Our approach conclusively identifies when species depart from their baseline phenological event timings and determines whether they experience novel environmental conditions or phenological mismatch with other species during their phenological event. In combination, these metrics detect emergence in timing, environment and community synchrony for species' phenological responses.
We explore these metrics using simulations then apply them to a diverse set of example datasets (butterflies, marine plankton and cherry blossoms). We then develop community-wide indicators of phenological emergence, environmental emergence and species mismatch, which can be applied to inform biodiversity policy at any scale and for any taxa.
These methods are available via the phenometrics R package.