Forecasting Phenology: Integrating Ecology, Climatology, and Phylogeny to Understand Plant Responses to Climate Change
Plant phenology, the timing of seasonal events such as budburst and ﬂowering, is an important indicator of climate change. Across the globe many plants have shifted their timings to track earlier springs and later autumns. Such shifts have important consequences because plant phenology is intimately linked with ecosystem services such as pol¬lination. Plant phenology is also linked with competition between diﬀerent species and individuals, and may thus shape plant and animal communities. Most research to date, however, has focused primarily on doc¬umenting species responses without developing a detailed understanding of why some species vary with climate and others do not. Our working group includes researchers from the ﬁelds of ecology, evolution, and climatology, and will use data from Europe and North America to improve our understanding of plant phenological responses to climate change. We will address a number of questions including:
(a) Do certain habitats, for example temperate forests or deserts, tend to show similar changes in plant phenology with climate change?
(b) Do plants that are closely related tend to show similar phenologies?
(c) Do short-term, small-scale experiments that increase temperatures and are designed to rep-resent climate change actually predict long-term trends?
This research should improve the design of future climate experiments, and should also help to pre¬dict which species are most vulnerable to extinction under climate change. Additionally, our work will develop new approaches for how to better use climate data in ecology and will inform the designs of government phenological data inventories and new citizen science projects such as Project BudBurst and the US National Phenological Network.
More information  about this research project and participants.
This work is supported by the National Center for Ecological Analysis and Synthesis, a Center funded by NSF (Grant #EF-0553768), the University of California, Santa Barbara, and the State of California.