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Climate-Driven Phenological Change: Developing Robust Spatiotemporal Modeling and Projection Capability
Stockholm University, Faculty of Science, Department of Physical Geography.
Stockholm University, Faculty of Science, Department of Physical Geography.
Number of Authors: 2
2015 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 10, no 11, e0141207Article in journal (Refereed) Published
Abstract [en]

Our possibility to appropriately detect, interpret and respond to climate-driven phenological changes depends on our ability to model and predict the changes. This ability may be hampered by non-linearity in climate-phenological relations, and by spatiotemporal variability and scale mismatches of climate and phenological data. A modeling methodology capable of handling such complexities can be a powerful tool for phenological change projection. Here we develop such a methodology using citizen scientists' observations of first flight dates for orange tip butterflies (Anthocharis cardamines) in three areas extending along a steep climate gradient. The developed methodology links point data of first flight observations to calculated cumulative degree-days until first flight based on gridded temperature data. Using this methodology we identify and quantify a first flight model that is consistent across different regions, data support scales and assumptions of subgrid variability and observation bias. Model application to observed warming over the past 60 years demonstrates the model usefulness for assessment of climate-driven first flight change. The cross-regional consistency of the model implies predictive capability for future changes, and calls for further application and testing of analogous modeling approaches to other species, phenological variables and parts of the world.

Place, publisher, year, edition, pages
2015. Vol. 10, no 11, e0141207
National Category
Earth and Related Environmental Sciences
Identifiers
URN: urn:nbn:se:su:diva-124180DOI: 10.1371/journal.pone.0141207ISI: 000364398700019PubMedID: 26545112OAI: oai:DiVA.org:su-124180DiVA: diva2:883240
Available from: 2015-12-16 Created: 2015-12-15 Last updated: 2015-12-16Bibliographically approved

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Prieto, CarmenDestouni, Georgia
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Department of Physical Geography
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