A Pollen Identification Key
While many pollen reference collections emphasize indigenous regional, often arboreal taxa, the Human Impacts Pollen Collection focuses on taxa relating to peoples’ impacts on the environment and landscape. These include cultivated and ornamental plants, but also ruderals, segetals, exotics, and invasives, which are often, although not exclusively, forbs, grasses, and shrubby taxa. This collection of pollen reference materials provides a tool for helping to identify the pollen from these types of plants and reconstruct changing vegetation patterns. The collection contains plants relating to human activities in the Caribbean, Iceland, and elsewhere, but focuses primarily on the North American landscape within the last 500 years. However, some of these taxa were introduced from Eurasia, Africa, and Australia. As such, the development of a database of these materials provides information that complements regionally-based collections that are focused on indigenous vegetation. The key has several thousand images of pollen from about 800 specimens.
Heather Trigg, Susan Jacobucci, Melody Henkel, and John Steinberg. With the assistance of Allison Conner, Kyle Edwards, Ciana Meyers, Sam Mrozowski, Marisa Patalano, Jessica Bowes, Michelle Garman, Tess Ostrowksy, Stephanie Hallinan and Alexandra Crowder.
How to Cite:
Trigg, H., S. Jacobucci, M. Henkel, and J. Steinberg. 2013. Human Impacts Pollen Database, an Illustrated Key. Andrew Fiske Center for Archaeological Research, University of Massachusetts Boston.
The authors would like to thank Kyle Port (Arnold Arboretum), Emily Wood (Gray Herbarium Harvard), Phil Tonne and Timothy Lowrey (University of New Mexico Herbarium), Lystigardurinn Arctic Botanical Gardens (Akureyri, Iceland), Debra Branker (Welchman Hall Gully, Barbados) for permission to collect flowers from their plants and herbarium sheets, and Robert Morris and Robert Stevenson (University of Massachusetts Boston) for advice with the creation and deployment of the key.
This research was supported by the National Science Foundation (Grant #1056364)