Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/24716
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dc.contributor.authorBush, ERen_UK
dc.contributor.authorAbernethy, Katharineen_UK
dc.contributor.authorJeffery, Kathryn Janeen_UK
dc.contributor.authorTutin, Caroline E Gen_UK
dc.contributor.authorWhite, Leeen_UK
dc.contributor.authorDimoto, Edmonden_UK
dc.contributor.authorDikangadissi, Jean-Thoussainten_UK
dc.contributor.authorJump, Alistairen_UK
dc.contributor.authorBunnefeld, Nilsen_UK
dc.date.accessioned2017-06-02T23:21:24Z-
dc.date.available2017-06-02T23:21:24Z-
dc.date.issued2017-05en_UK
dc.identifier.urihttp://hdl.handle.net/1893/24716-
dc.description.abstractChanges in phenology are an inevitable result of climate change, and will have wide-reaching impacts on species, ecosystems, human society and even feedback onto climate. Accurate understanding of phenology is important to adapt to and mitigate such changes. However, analysis of phenology globally has been constrained by lack of data, dependence on geographically limited, non-circular indicators and lack of power in statistical analyses.  To address these challenges, especially for the study of tropical phenology, we developed a flexible and robust analytical approach - using Fourier analysis with confidence intervals - to objectively and quantitatively describe long-term observational phenology data even when data may be noisy. We then tested the power of this approach to detect regular cycles under different scenarios of data noise and length using both simulated and field data.  We use Fourier analysis to quantify flowering phenology from newly available data for 856 individual plants of 70 species observed monthly since 1986 at Lopé National Park, Gabon. After applying a confidence test, we find that 59% of the individuals have regular flowering cycles, and 88% species flower annually. We find time series length to be a significant predictor of the likelihood of confidently detecting a regular cycle from the data. Using simulated data we find that cycle regularity has a greater impact on detecting phenology than event detectability. Power analysis of the Lopé field data shows that at least six years of data are needed for confident detection of the least noisy species, but this varies and is often greater than 20 years for the most noisy species.  There are now a number of large phenology datasets from the tropics, from which insights into current regional and global changes may be gained, if flexible and quantitative analytical approaches are used. However consistent long-term data collection is costly and requires much effort. We provide support for the importance of such research and give suggestions as to how to avoid erroneous interpretation of shorter length datasets and maximize returns from long-term observational studies.en_UK
dc.language.isoenen_UK
dc.publisherWiley-Blackwellen_UK
dc.relationBush E, Abernethy K, Jeffery KJ, Tutin CEG, White L, Dimoto E, Dikangadissi J, Jump A & Bunnefeld N (2017) Fourier analysis to detect phenological cycles using long-term tropical field data and simulations. Methods in Ecology and Evolution, 8 (5), pp. 530-540. https://doi.org/10.1111/2041-210X.12704en_UK
dc.relation.urihttp://hdl.handle.net/11667/83en_UK
dc.rightsThis item has been embargoed for a period. During the embargo 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. This is the peer reviewed version of the following article: Bush, E. R., Abernethy, K. A., Jeffery, K., Tutin, C., White, L., Dimoto, E., Dikangadissi, J.-T., Jump, A. S. and Bunnefeld, N. (2017), Fourier analysis to detect phenological cycles using long-term tropical field data and simulations. Methods Ecol Evol, 8: 530–540, which has been published in final form at https://doi.org/10.1111/2041-210X.12704. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.en_UK
dc.subjectFloweringen_UK
dc.subjectPhenophasesen_UK
dc.subjectSpectral analysisen_UK
dc.subjectTropical forestsen_UK
dc.subjectGabonen_UK
dc.subjectTime-series dataen_UK
dc.subjectClimate change, Circular analysisen_UK
dc.subjectLopé National parken_UK
dc.titleFourier analysis to detect phenological cycles using long-term tropical field data and simulationsen_UK
dc.typeJournal Articleen_UK
dc.rights.embargodate2017-12-14en_UK
dc.rights.embargoreason[Bush et al. Fourier for tropical phenology 2016.11.1.pdf] Publisher requires embargo of 12 months after formal publication.en_UK
dc.identifier.doi10.1111/2041-210X.12704en_UK
dc.citation.jtitleMethods in Ecology and Evolutionen_UK
dc.citation.issn2041-210Xen_UK
dc.citation.volume8en_UK
dc.citation.issue5en_UK
dc.citation.spage530en_UK
dc.citation.epage540en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.author.emaile.r.bush@stir.ac.uken_UK
dc.citation.date13/12/2016en_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.contributor.affiliationUniversity of Stirlingen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.contributor.affiliationCentre International de Recherches Médicales de Francevilleen_UK
dc.contributor.affiliationCentre International de Recherches Médicales de Francevilleen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.identifier.isiWOS:000400823400001en_UK
dc.identifier.scopusid2-s2.0-85006765623en_UK
dc.identifier.wtid545638en_UK
dc.contributor.orcid0000-0003-4036-125Xen_UK
dc.contributor.orcid0000-0002-0393-9342en_UK
dc.contributor.orcid0000-0002-2632-0008en_UK
dc.contributor.orcid0000-0002-2167-6451en_UK
dc.contributor.orcid0000-0002-1349-4463en_UK
dc.date.accepted2016-10-30en_UK
dcterms.dateAccepted2016-10-30en_UK
dc.date.filedepositdate2016-12-16en_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionAMen_UK
local.rioxx.authorBush, ER|0000-0003-4036-125Xen_UK
local.rioxx.authorAbernethy, Katharine|0000-0002-0393-9342en_UK
local.rioxx.authorJeffery, Kathryn Jane|0000-0002-2632-0008en_UK
local.rioxx.authorTutin, Caroline E G|en_UK
local.rioxx.authorWhite, Lee|en_UK
local.rioxx.authorDimoto, Edmond|en_UK
local.rioxx.authorDikangadissi, Jean-Thoussaint|en_UK
local.rioxx.authorJump, Alistair|0000-0002-2167-6451en_UK
local.rioxx.authorBunnefeld, Nils|0000-0002-1349-4463en_UK
local.rioxx.projectInternal Project|University of Stirling|https://isni.org/isni/0000000122484331en_UK
local.rioxx.freetoreaddate2017-12-14en_UK
local.rioxx.licencehttp://www.rioxx.net/licenses/under-embargo-all-rights-reserved||2017-12-13en_UK
local.rioxx.licencehttp://www.rioxx.net/licenses/all-rights-reserved|2017-12-14|en_UK
local.rioxx.filenameBush et al. Fourier for tropical phenology 2016.11.1.pdfen_UK
local.rioxx.filecount1en_UK
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