Please use this identifier to cite or link to this item: http://hdl.handle.net/11667/83
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dc.contributorBush, Emma-
dc.contributor.otherAgence Nationale des Parcs Nationaux (ANPN) (2010-2016)en_GB
dc.contributor.otherImpact Studentship funded by the University of Stirling and ANPN (2013-2016)-
dc.contributor.otherInternational Centre for Medical Research in Franceville (CIRMF) (1986-2010)-
dc.coverage.spatialLopé National Park, Gabonen_GB
dc.coverage.temporal1986-2016en_GB
dc.creatorBush, Emma R-
dc.creatorAbernethy, Katharine-
dc.creatorJeffery, Kathryn Jane-
dc.creatorTutin, Caroline EG-
dc.creatorWhite, Lee-
dc.creatorDimoto, Edmond-
dc.creatorDikangadissi, Jean-Thoussaint-
dc.creatorJump, Alistair S-
dc.creatorBunnefeld, Nils-
dc.date.accessioned2016-11-03T15:59:10Z-
dc.date.available2016-11-03T15:59:10Z-
dc.date.created2016-10-30-
dc.identifier.urihttp://hdl.handle.net/11667/83-
dc.description.abstractData to accompany manuscript Bush et al. Accepted in Methods in Ecology and Evolution October 2016. Fourier analysis to detect phenological cycles using tropical field data and simulations. Abstract for the publication is: 1.Changes 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. 2. 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. 3. 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. 4. 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_GB
dc.description.tableofcontents(1.) Fourier_outputs_for_each_individual_tree.csv - Spreadsheet of Fourier outputs for each individual tree (2.) Fourier_outputs_for_each_individual_tree_metadata.csv - Spreadsheet with metadata for 'Fourier_outputs_for_each_individual_tree.csv' (3.) Fourier_outputs_summarised_for_each_species.csv - Spreadsheet of Fourier outputs summarised for each species (4.) Fourier_outputs_summarised_for_each_species_metadata.csv - Spreadsheet with metadata for 'Fourier_outputs_summarised_for_each_species.csv'en_GB
dc.language.isoengen_GB
dc.publisherUniversity of Stirling. Faculty of Natural Sciences.en_GB
dc.relationBush, ER; Abernethy, K; Jeffery, KJ; Tutin, CEG; White, L; Dimoto, E; Dikangadissi, J-T; Jump, AS; Bunnefeld, N (2016): Dataset: Fourier analysis to detect phenological cycles using tropical field data and simulations. University of Stirling. Faculty of Natural Sciences. Dataset. http://hdl.handle.net/11667/83en_GB
dc.relation.isreferencedbyBush, E.R.; Abernethy, K., Jeffery, K.J., Tutin, C.E.G, White, L., Dimoto, E., Dikangadissi, J-T., Jump, A, Bunnefeld, N. (2017) Fourier analysis to detect phenological cycles using tropical field data and simulations. Methods in Ecology and Evolution, 8 (5), pp. 530-540. DOI: https://doi.org/10.1111/2041-210X.12704 Available from: http://hdl.handle.net/1893/24716en_GB
dc.rightsRights covered by the standard CC-BY 4.0 licence: https://creativecommons.org/licenses/by/4.0/en_GB
dc.sourceThe Lopé longterm observational phenology study (1986-2016)en_GB
dc.subjectFloweringen_GB
dc.subjectPhenophasesen_GB
dc.subjectSpectral analysisen_GB
dc.subjectTropical forestsen_GB
dc.subjectGabonen_GB
dc.subjectTime-series dataen_GB
dc.subjectClimate changeen_GB
dc.subjectCircular analysisen_GB
dc.subjectLopé National Parken_GB
dc.subject.classification::Ecology, biodiversity and systematics::Conservation Ecologyen_GB
dc.titleDataset: Fourier analysis to detect phenological cycles using tropical field data and simulationsen_GB
dc.typedataseten_GB
dc.contributor.emailk.a.abernethy@stir.ac.uken_GB
dc.identifier.rmsid626en_GB
dc.identifier.projectidGABON - 04962en_GB
dc.identifier.projectid00045-
dc.title.projectGABON: maintain long-standing scientific profileen_GB
dc.contributor.affiliationUniversity of Stirling (Biological and Environmental Sciences)en_GB
dc.contributor.affiliationInstitut de Recherche en Écologie Tropicale, Gabonen_GB
dc.contributor.affiliationAgence Nationale des Parcs Nationaux (ANPN), Gabonen_GB
dc.date.publicationyear2016-
Appears in Collections:University of Stirling Research Data

Files in This Item:
File Description SizeFormat 
Fourier_outputs_for_each_individual_tree.csvSpreadsheet of Fourier outputs for each individual tree67.81 kBCSVView/Open
Fourier_outputs_for_each_individual_tree_metadata.csvSpreadsheet with metadata for 'Fourier_outputs_for_each_individual_tree.csv'1.81 kBCSVView/Open
Fourier_outputs_summarised_for_each_species.csvSpreadsheet of Fourier outputs summarised for each species4.66 kBCSVView/Open
Fourier_outputs_summarised_for_each_species_metadata.csvSpreadsheet with metadata for 'Fourier_outputs_summarised_for_each_species.csv'1.87 kBCSVView/Open


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