Please use this identifier to cite or link to this item: http://hdl.handle.net/11667/92
Appears in Collections:University of Stirling Research Data
Title: Dataset: Towards effective monitoring of tropical phenology
Creator(s): Bush, Emma R
Bunnefeld, Nils
Dimoto, Edmond
Dikangadissi, Jean-Thoussaint
Jeffery, Kathryn Jane
Tutin, Caroline E G
White, Lee
Abernethy, Katharine
Contact Email: e.r.bush@stir.ac.uk
Keywords: Tropical forests
Tropical phenology
Long-term monitoring
Climate-change
Congo basin forest
Fourier
Observation uncertainty
Date Available: 14-Jun-2017
Citation: Bush, ER; Bunnefeld, N; Dimoto, E; Dikangadissi, J-T; Jeffery, KJ; Tutin, CEG; White, L; Abernethy, K (2017): Dataset: Towards effective monitoring of tropical phenology. University of Stirling. Dataset. http://hdl.handle.net/11667/92
Publisher: University of Stirling
Dataset Description (Abstract): Data to accompany manuscript, Bush et al., "Towards effective monitoring of tropical phenology: maximising returns and reducing uncertainty in long-term studies”. Abstract for the publication is: Phenology is a key component of ecosystem function and is increasingly included in assessments of ecological change. We consider how existing, and emerging, tropical phenology monitoring programs can be made most effective by investigating major sources of noise in data collection at a long-term study site. Researchers at Lopé NP, Gabon, have recorded monthly crown observations of leaf, flower and fruit phenology for 88 plant species since 1984. For a subset of these data, we first identified dominant regular phenological cycles, using Fourier analysis, and then tested the impact of observation uncertainty on cycle detectability, using expert knowledge and generalized linear mixed modelling (827 individual plants of 61 species). We show that experienced field observers can provide important information on major sources of noise in data collection and that observation length, phenophase visibility and duration are all positive predictors of cycle detectability. We find that when a phenological event lasts > 4 weeks, an additional 10 years of data increases cycle detectability by 114 percent and that cycle detectability is 92 percent higher for the most visible events compared to the least. We also find that cycle detectability is four times as high for flowers compared to ripe fruits after 10 years. To maximise returns in the short-term, resources for long-term monitoring of phenology should be targeted towards highly visible phenophases and events that last longer than the observation interval. In addition, programs that monitor flowering phenology are likely to accurately detect regular cycles more quickly than those monitoring fruits, thus providing a baseline or future assessments of change.
Dataset Description (TOC): (1.) Fourier_outputs_for_each_individual_tree_phenophase.csv - Spreadsheet of Fourier outputs for each individual tree and phenophase (2.) Fourier_outputs_for_each_individual_tree_phenophase_metadata.csv - Spreadsheet with metadata for 'Fourier_outputs_for_each_individual_tree_phenophase.csv' (3.) Observer_scores_by_species_phenophase.csv - Spreadsheet of observer scores for each species and phenophase (4.) Observer_scores_by_species_phenophase_metdata.csv - Spreadsheet with metadata for 'Observer_scores_by_species_phenophase.csv'
Type: dataset
Contract/Grant Title: GABON: maintain long-standing scientific profile
Funder(s): Agence Nationale des Parcs Nationaux (ANPN) (2010-2016)
Impact Studentship funded by the University of Stirling and ANPN (2013-2016)
International Centre for Medical Research in Franceville (CIRMF) (1986-2010)
Contract/Grant Number: GABON - 04962
00045
Geographic Location(s): Lopé National Park, Gabon
Time Period: 1986-2016
URI: http://hdl.handle.net/11667/92
Rights: Rights covered by the standard CC-BY 4.0 licence: https://creativecommons.org/licenses/by/4.0/
Affiliation(s) of Dataset Creator(s): University of Stirling (Biological and Environmental Sciences)
Agence Nationale des Parcs Nationaux (ANPN)
National Centre of Scientific and Technological Research (CENAREST)

Files in This Item:
File Description SizeFormat 
Fourier_outputs_by_individual_tree_phenophase.csvSpreadsheet of Fourier outputs for each individual tree and phenophase290.56 kBUnknownView/Open
Fourier_outputs_by_individual_tree_phenophase_metadata.csvSpreadsheet with metadata for 'Fourier_outputs_for_each_individual_tree_phenophase.csv'987 BUnknownView/Open
ObserverScoresBySpeciesPhenophase.csvSpreadsheet of observer scores for each species and phenophase10.39 kBUnknownView/Open
Observer_scores_by_species_phenophase_metadata.csvSpreadsheet with metadata for 'Observer_scores_by_species_phenophase.csv'680 BUnknownView/Open


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