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: Towards effective monitoring of tropical phenological change: maximising returns and reducing uncertainty in long-term studies
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): Towards effective monitoring of tropical phenological change: maximising returns and reducing uncertainty in long-term studies. 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 phenological change: maximising returns and reducing uncertainty in long-term studies" Abstract for the publication is: Phenology datasets are increasingly used to assess climate-induced changes in tropical ecosystem function. We ask: How can existing and future phenology monitoring programs be made most effective for this purpose? Researchers at Lopé NP, Gabon, have recorded monthly crown observations of leaf, flower and fruit phenology for 88 plant species since 1984. We used Fourier analysis combined with a confidence test to detect dominant regular cycles using these data. We also gathered expert knowledge on the visibility and duration of each phenological event for every species and used generalized linear mixed modelling to test the impact of observation uncertainty on the likelihood of detecting a cycle. We show that experienced field observers can easily quantify major sources of observation uncertainty and that phenophase visibility and duration, alongside observation length, are 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 visible. 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 change should be targeted towards highly visible species and phenological events that last longer than the observation interval. In resource-restricted contexts where the aim of research is to assess climate-induced changes to plant productivity, programs that favour monitoring flowers over fruits are likely to detect flowering change in a shorter time-frame.
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): Biological and Environmental Sciences
National Centre of Scientific and Technological Research (CENAREST)
Agence Nationale des Parcs Nationaux (ANPN)

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
Observer_scores_by_species_phenophase.csvSpreadsheet of observer scores for each species and phenophase10.38 kBUnknownView/Open
Observer_scores_by_species_phenophase_metadata.csvSpreadsheet with metadata for 'Observer_scores_by_species_phenophase.csv'680 BUnknownView/Open


This item is protected by original copyright



Items in DataSTORRE are protected by copyright, with all rights reserved, unless otherwise indicated.