Inter-annual variability of fruit timing and quantity at Nouragues (French Guiana): insights from hierarchical Bayesian analyses. Supporting data

dc.contributor.authorMendoza, Irene
dc.contributor.authorCondit, Richard S.
dc.contributor.authorWright, S. Joseph
dc.contributor.authorCaubère, Adeline
dc.contributor.authorChâtelet, Patrick
dc.contributor.authorHardy, Isabelle
dc.contributor.authorForget, Pierre-Michel
dc.date.accessioned2018-02-15T15:51:55Z
dc.date.available2018-02-15T15:51:55Z
dc.date.issued2018
dc.description.abstractThe timing and quantity of fruit production are major determinants of the functioning of a forest community, but both components are rarely taken into account simultaneously. We aimed at determining fruiting variability in timing and quantity in a rainforest community at two temporal scales: seasonal and inter-annual. We also examined whether dispersal type may influence fruiting variation. We developed a hierarchical Bayesian approach for analyzing a ten-year dataset (2001-2011) of fruit phenology (45 tree and liana species) from the Amazonian forest of Nouragues (French Guiana), with a 29% of censuses lacking. Regarding annual seasonality, the fruiting peak of 49% of species was reached during the peak of the rainy season, which is the most typical pattern of central and eastern Amazon. Most species varied across years in both timing and quantity of fruiting, although seed production showed larger changes. We did not find significant differences in inter-annual variation on fruiting according to the dispersal mode of species. Parameters extracted from the Bayesian models were helpful to classify species according to their degree of variability (low, medium and high) and to distinguish masting events (40% of species). Seed rain at the community level was dominated by 25% of species, which overwhelmingly had abiotic dispersal modes (80%). Our analytical method proved helpful to explore inter-annual variability of the large majority of species in the community, although showed a poor fit for two continuous species. It also allowed overcoming the analytical challenge of lacking censuses, which is a common problem in tropical monitoring. The combination of long-term monitoring of phenology with sophisticated statistical analyses is therefore key for a better understanding of temporal changes in fruiting phenology. Future development of our models will allow forecasting of fruit variation under new climatic conditions, which has critical consequences for depending consumers.
dc.formattext
dc.identifier.citationMendoza, Irene, Condit, Richard S., Wright, S. Joseph, Caubère, Adeline, Châtelet, Patrick, Hardy, Isabelle, and Forget, Pierre-Michel. 2018. [Dataset] Inter-annual variability of fruit timing and quantity at Nouragues (French Guiana): insights from hierarchical Bayesian analyses. Supporting data. [text] Distributed by Edgewater, Maryland: Smithsonian Tropical Research Institute. <a href="https://doi.org/10.25570/STRI/10088/35071">https://doi.org/10.25570/STRI/10088/35071</a>.
dc.publisherSmithsonian Tropical Research Institute
dc.subjectAmazon Basinen
dc.subjectdispersal modesen
dc.subjectfrugivoryen
dc.subjectlong-term monitoringen
dc.subjectphenologyen
dc.subjectrain foresten
dc.subjectseed productionen
dc.titleInter-annual variability of fruit timing and quantity at Nouragues (French Guiana): insights from hierarchical Bayesian analyses. Supporting data
dc.typedataset
sro.description.unitstri
sro.description.unitdataset
sro.identifier.doi10.25570/STRI/10088/35071
sro.identifier.itemID145305
sro.identifier.refworksID60201
sro.publicationPlaceEdgewater, Maryland

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