Primary Research Article
Food web de-synchronization in England's largest lake: an assessment based on multiple phenological metrics
Article first published online: 23 AUG 2013
© 2013 John Wiley & Sons Ltd
Global Change Biology
Volume 19, Issue 12, pages 3568–3580, December 2013
How to Cite
Thackeray, S. J., Henrys, P. A., Feuchtmayr, H., Jones, I. D., Maberly, S. C. and Winfield, I. J. (2013), Food web de-synchronization in England's largest lake: an assessment based on multiple phenological metrics. Global Change Biology, 19: 3568–3580. doi: 10.1111/gcb.12326
- Issue published online: 8 NOV 2013
- Article first published online: 23 AUG 2013
- Accepted manuscript online: 19 JUL 2013 05:16AM EST
- Manuscript Accepted: 12 JUL 2013
- Manuscript Revised: 11 JUL 2013
- Manuscript Received: 27 OCT 2012
- Centre for Ecology & Hydrology Environmental Change Integrating Fund Project
- SPACE (Shifting Phenology: Attributing Change across Ecosystems)
- NERC. Grant Numbers: NE/H000208/1, NE/J02080X/1
|gcb12326-sup-0001-FigS1.tif||image/tif||66K||Figure S1. Rates of phenological change (1969–2008) across three trophic levels in (a) the North Basin and (b) the South Basin of Windermere, UK.|
|gcb12326-sup-0002-FigS2.tif||image/tif||120K||Figure S2. Examples of long-term change in the seasonal time difference between events at different trophic levels in the North and South basins of Windermere.|
|gcb12326-sup-0003-FigS3.pdf||application/PDF||84K||Figure S3. Long-term variations in potential physical drivers of phenological change.|
|gcb12326-sup-0004-FigS4.pdf||application/PDF||77K||Figure S4. Long-term variations in potential chemical and biological drivers of phenological change.|
|gcb12326-sup-0005-TablesS1-S5-DataS1.docx||Word document||42K|| |
Table S1. The phenological metrics used to quantify the seasonal timing of plankton development and perch spawning.
Table S2. Driving variables used in the analyses of phenological change, with justification for their inclusion and supporting references.
Table S3. Comparison of phenological metrics derived using filter count and microscope data for Daphnia.
Table S4. Summaries of exemplar linear models of long-term changes in the seasonal time difference between phenological events at adjacent trophic levels.
Table S5. Correlation matrix for predictors included in the hierarchical modelling of phenological change at three trophic levels.
Data S1. Hierarchical model structure for analysis of drivers.
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