Data from biotic variability and synchrony across hierarchical levels and freshwater networks
Data files
Sep 29, 2025 version files 95.56 KB
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README.md
2.51 KB
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The_data_supporting_the_results_of_the_manuscript.xlsx
93.05 KB
Oct 20, 2025 version files 147.77 KB
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Fig3.R
4.27 KB
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Fig4.R
19.96 KB
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Fig5.R
16.60 KB
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README.md
2.86 KB
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The_data_supporting_the_results_of_the_manuscript.xlsx
93.05 KB
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var_part.R
11.03 KB
Abstract
Understanding temporal variability and synchrony across biological hierarchical levels (from species to metacommunities) and ecosystems, and their underlying drivers, remains a fundamental ecological question. However, most studies are performed within an ecosystem, overlooking the complexity structuring natural high-level metacommunities across ecosystems. By applying theoretical frameworks of metacommunity variability with phytoplankton datasets across a pond-stream-lake continuum, we show that (i) temporal variability decreases from species to metacommunities, while synchrony exhibits complex hierarchical patterns and varies depending on spatial scales; (ii) temporal variability and synchrony are lower in streams than ponds or the lake, and spatiotemporal community-environment relationships are stronger in the lake than the ponds or streams. These patterns are strongly related to environmental fluctuations, dispersal and species diversity. Our study advances the theoretical and empirical understanding of how complex biological hierarchies and freshwater networks influence biotic variability and synchrony, providing valuable insights for aquatic biodiversity conservation.
Title: biotic variability and synchrony across hierarchical levels and freshwater networks
We have submitted our raw data (The data supporting the results of the manuscript.xlsx).
Description of files:
The data are compiled in an Excel spreadsheet (i.e., The data supporting the results of the manuscript.xlsx) with 10 tabs containing the following information:
- Fig.3_data, data supporing for Fig.3;
- Fig.4_data, data supporing for Fig.4;
- Fig.5ABC_data, data supporing for Fig.5ABC;
- Fig.5DEF_data, data supporing for Fig.5DEF;
- Fig.5GHI_data, data supporing for Fig.5GHI;
- Fig.5JKL_data, data supporing for Fig.5JKL;
- Fig.5MNO_data, data supporing for Fig.5MNO;
- Richness_data，data may be interesting for audiences
- Cell density_data，data may be interesting for audiences
- Species list_data，data may be interesting for audiences
Variables:
Species variability: temporal variability in abundance at species level (Note overall that abundance is cell density (cells/mL))
Community variability: temporal variability in abundance at community level
Low-level metaommunity variability: temporal variability in abundance within a low-level metacommunity
High-level metaommunity variability: temporal variability in abundance within a high-level metacommunity
Species synchrony: synchrony of species abundance within a local community
Community synchrony: spatial synchrony of total community abundance among local communities
Low-level metaommunity synchrony: spatial synchrony of total metacommunity abundance among low-level metacommunities
Dataset: dataset of phytoplankton samples
Freshwater network: freshwater network along a pond-stream-lake continuum
Environment control: explanatory power (%) for environmental factors on spatiotemporal community dissimilarity
Distance to centroid: environmental distance of sites and times to group (a freshwater network) centroid
Correlation of environmental fluctuations: between-site correlation in temporal environmental fluctuations (temporal environmental changes within each of these sampling sites)
Shared proportions: pairwise shared proportion (%) of phytoplankton species between sites
Connectance: connectance of species-patch networks
Simpson's diversity: Phytoplankton Simpson diversity
Site_ID: unique ID of the sampling site
Average richness: average phytoplankton richness for each sampling site
Average cell density: average phytoplankton cell density (cells/mL) for each sampling site
Species: identification of the phytoplankton at the species level
R Code to plot figures 3, 4, 5 and calculate variability and synchrony across hierarchical levels:
- Fig3.R, R Code to plot Fig.3;
- Fig4.R, R Code to plot Fig.4;
- Fig5.R, R Code to plot Fig.5;
- var_part.R, R Code to calculate variability and synchrony across hierarchical levels
Changes after Sep 29, 2025: we added the R code to plot figures 3, 4, 5 and calculate variability and synchrony across hierarchical levels