five

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

收藏
Figshare2018-02-15 更新2026-04-28 收录
下载链接:
https://figshare.com/articles/dataset/Inter-annual_variability_of_fruit_timing_and_quantity_at_Nouragues_French_Guiana_insights_from_hierarchical_Bayesian_analyses_Supporting_data/25620903
下载链接
链接失效反馈
官方服务:
资源简介:
The 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.
创建时间:
2018-02-15
二维码
社区交流群
二维码
科研交流群
商业服务