http://hdl.handle.net/1893/28786
Appears in Collections: | Biological and Environmental Sciences Journal Articles |
Peer Review Status: | Refereed |
Title: | Unbiased inference of plant flowering phenology from biological recording data |
Author(s): | Chapman, Daniel S Bell, Sandra Helfer, Stephan Roy, David B |
Contact Email: | daniel.chapman@stir.ac.uk |
Keywords: | Bayesian model citizen science climate change discrete Fourier transform growing degree days phenology model recorder effort |
Issue Date: | 31-Jul-2015 |
Date Deposited: | 11-Feb-2019 |
Citation: | Chapman DS, Bell S, Helfer S & Roy DB (2015) Unbiased inference of plant flowering phenology from biological recording data. Biological Journal of the Linnean Society, 115 (3), pp. 543-554. https://doi.org/10.1111/bij.12515 |
Abstract: | Phenology is a key indicator and mediator of the ecological impacts of climate change. However, studies monitoring the phenology of individual species are moderate in number, taxonomically and geographically restricted, and mainly focused on spring events. As such, attention is being given to nonstandard sources of phenology data, such as the dates of species' biological records. Here, we present a conceptual framework for deriving phenological metrics from biological recording data, while accounting for seasonal variation in the level of activity by recorders. We develop a new Bayesian statistical model to infer the seasonal pattern of plant 'recordability'. The modelled dates of maximum recordability are strongly indicative of the flowering peaks of 29 insect-pollinated species monitored in two botanic gardens in Great Britain. Conversely, not accounting for the seasonality in recording activity results in biased estimates of the observed flowering peaks. However, observed first and last flowering dates were less reliably explained by the model, which probably reflects greater interspecific variation in levels of recording before and after flowering. We conclude that our method provides new potential for gaining useful insights into large-scale variation in peak phenology across a much broader range of plant species than have previously been studied. |
DOI Link: | 10.1111/bij.12515 |
Rights: | The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. |
Licence URL(s): | http://www.rioxx.net/licenses/under-embargo-all-rights-reserved |
File | Description | Size | Format | |
---|---|---|---|---|
Chapman et al-BJLS-2015.pdf | Fulltext - Published Version | 955.34 kB | Adobe PDF | Under Permanent Embargo Request a copy |
Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.
This item is protected by original copyright |
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved https://creativecommons.org/publicdomain/zero/1.0/
If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.