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Published May 29, 2022 | Version 1.0
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Code and data: Ecological stability propagates across spatial scales and trophic levels in freshwater ecosystems

  • 1. São Paulo State University (UNESP)
  • 2. Utah State University
  • 3. University of Washington
  • 4. University of Canterbury
  • 5. Illinois State University
  • 6. Federal University of São Carlos
  • 7. Southern Illinois University Edwardsville
  • 8. Universitat de Barcelona
  • 9. Maringá State University
  • 10. Institute of Environmental Assessment and Water Research (IDAEA)
  • 11. INRAE
  • 12. Murray State University
  • 13. University of Wisconsin Madison
  • 14. University of Duisburg-Essen
  • 15. University of Huddersfield
  • 16. The Ohio State University
  • 17. University of Oulu
  • 18. Northumbria University
  • 19. University of California, Davies
  • 20. Masaryk University
  • 21. International Institute for Sustainable Development Experimental Lakes Area
  • 22. Virginia Institute of Marine Science
  • 23. Norwegian Institute for Water Research
  • 24. T.G. Masaryk Water Research Institute p.r.i.
  • 25. University of California, Berkeley

Description

The files listed below include data and code used to produce the results, including those made available as supplementary material, described in Siqueira et al. (https://ecoevorxiv.org/mpf5x), "Ecological stability propagates across spatial scales and trophic levels in freshwater ecosystems".

The full set of results can be reproduced by running four R codes following this sequence:

- 01_Siqueira_etal_dataprep_stability_metrics.R
- 02_Siqueira_etal_SEM_analyses.R
- 03_Siqueira_etal_stab_figs.R
- 04_Siqueira_etal_stab_supp_m.R

To run the first R code (“01_Siqueira_etal_dataprep_stability_metrics.R”), 3 .csv files are needed.

"data_stab_analysis_except_lepas.csv" has 151404 rows and 17 columns. Rows represent the abundance (individual counts, biomass, coverage area) of a given taxon, at a given site, in a given year. Some abundance values were generated by interpolation (see details in the Methods section of the paper and supplementary material). The 17 columns include


"Data_set_ID": a numerical vector describing 34 of the 35 independent metacommunity data sets. For the 35th data set, see below.    
"Metacom": a character vector describing 34 of the 35 independent metacommunity data sets. This column was kept for the sake of preserving the original identity of each data set.
"Sample_id": a vector representing a unique combination of data set ID, site ID, and time step.
"Site": a vector describing the ID of the site where the sample was taken.
"Year": a vector describing the year when the sample was taken.        
 "Frequency": a vector describing the frequency interval at which the samples were taken. This variable has only one state (“Inter_annual”) and was kept because some of the data originally gathered (before filtering) included also intra-annual sampling (these were discarded).
"Time_step": a vector describing the time step a sample was taken, considering the whole number of years included in that data set.
"Lat": a vector describing the latitude of the sampling site in decimal degrees.          
"Long": a vector describing the latitude of the sampling site in decimal degrees.

"Datum": a vector describing the datum used by the person who collected the sample.       
"Coord_system": a vector describing the coordinate system used in this data set after data cleaning.
"Bio_gr": a vector describing the major biological groups in the data set (e.g., macroinvertebrates, fish).
"Ecosys": a vector describing the two ecosystem types in the data set (streams and lakes).        "Species": a vector describing the species or genus names.
"Abundance": a vector describing species or genus abundance, density, or coverage.    
"Trophic_gr": a vector describing 3 broad trophic groups (producers, consumers that are invertebrates, and consumers that are vertebrates).    
"New_tr_g": a vector describing 5 trophic levels used in the analysis (producers, primary consumers secondary consumers, tertiary consumers).

The following files were made available separately due to the data sharing policies of The Ohio Division of Wildlife (ODOW). Thus, we made them available not in the format of raw numbers, but as pre-processed variables that we used in our models (e.g., stability and diversity metrics, trophic groups, etc.).  

"lepas_site_stab_metrics.csv" has 8 rows and 14 columns. Rows represent sites sampled for a given trophic level. Columns include "Lat", "Long", "Metacom", "Sample_id", "Site", "Bio_gr", "Ecosys", and "New_tr_g" as described above and:
"Site_troph": a vector representing a combination of site ID and trophic level. This was used to identify sites that include more than one trophic level.               
"Simp": a vector describing the Simpson diversity index of a sampled site.                  
"synchrony_comm_site": a vector describing species population synchrony within a sampled site.  
"mean_cv_species_site": a vector describing the average coefficient of variation of species sampled in a site.
"cv_comm_site": a vector describing local temporal variability of aggregated community abundance.
"S": a vector describing species richness in a sampled site.

"lepas_meta_stab_metrics.csv" has 1 row and 21 columns. The row represents the LEPAS metacommunity. Columns include "Metacom", "Freq", "Time_step", "Bio_gr", "Trophic_gr", "New_tr_g", and "Ecosys" as described above and:
"Meta_troph": a vector representing a combination of metacommunity ID and trophic level. This was used to differentiate metacommunities that include more than one trophic level.               
 "Simp": a vector describing the Simpson diversity index averaged across sites within the metacommunity.  
"S": a vector describing the species richness averaged across sites within the metacommunity.                
"nSites": a vector describing the number of sampled sites in the metacommunity.                
"CV_S_L": a vector describing population temporal variability (sensu Wang et al. 2019) within metacommunity.                
"CV_C_L": a vector describing community temporal variability (sensu Wang et al. 2019) within metacommunity.                
"CV_S_R": a vector describing metapopulation temporal variability (sensu Wang et al. 2019) within metacommunity.
"CV_C_R": a vector describing metacommunity temporal variability (sensu Wang et al. 2019).
"phi_S_L2R": a vector describing species-level spatial synchrony (sensu Wang et al. 2019) within metacommunity.
"phi_C_L2R": a vector describing community-level spatial synchrony (sensu Wang et al. 2019) within metacommunity.
"phi_S2C_L": a vector describing local-scale species synchrony (sensu Wang et al. 2019) within metacommunity.
"phi_S2C_R": a vector describing regional-scale species synchrony (sensu Wang et al. 2019) within metacommunity.
"Simp_gamma": a vector describing Simpson gamma diversity in the metacommunity.
"S_gamma": a vector describing regional richness in the metacommunity.

To run the second R code (“02_Siqueira_etal_SEM_analyses.R”), two groups of files are needed – one group of files prepared with the first code and the following two .csv files:

"site_env_preds.csv" has 735 rows and 3 columns. Rows represent climatic data extracted from each of the sites used in analyses. The 3 columns include:
"Site_troph": a vector representing a combination of site ID and trophic level. This was used to identify sites that include more than one trophic level.               
"bio4": a numerical vector describing seasonality in temperature in each site.  
"bio15": a numerical vector describing seasonality in precipitation in each site.

"meta_env_spa_preds.cs" has 59 rows and 4 columns. Rows represent each of the sites used in analyses. The 4 columns include:
"Meta_troph": a vector representing a combination of metacommunity ID and trophic level. This was used to differentiate metacommunities that include more than one trophic level.               
"Tmax_sync ": a numerical vector describing synchrony in maximum temperature within the metacommunity.  
"Tmin_sync ": a numerical vector describing synchrony in minimum temperature within the metacommunity.
"Precip_sync ": a numerical vector describing synchrony in precipitation within the metacommunity.  

To run the third and fourth R codes (“03_Siqueira_etal_stab_figs.R”; “04_Siqueira_etal_stab_supp_m.R”), one needs the same files described above.

 

Notes

Acknowledgments. T.S. was supported by grants #19/04033-7 and #21/00619-7, São Paulo Research Foundation (FAPESP), and by grant #309496/2021-7, Brazilian National Council for Scientific and Technological Development (CNPq). Participation by CPH was supported, in part, by US National Science Foundation grant IOS-1754838. CPH thanks the PacFish/InFish Biological Opinion Monitoring Program (administered by the US Forest Service) for use of their long-term macroinvertebrate monitoring data. JDT is supported by a Rutherford Discovery Fellowship administered by the Royal Society Te Apārangi (RDF-18-UOC-007), and Bioprotection Aotearoa and Te Pūnaha Matatini, both Centres of Research Excellence funded by the Tertiary Education Commission, New Zealand. VS was supported by a FAPESP grant #2019/06291-3 during the writing of this manuscript. The FEHM (Freshwater Ecology, Hydrology and Management) research group is funded by the "Agència de Gestió d'Ajuts Universitaris i de Recerca" (AGAUR) at the "Generalitat de Catalunya" (2017SGR1643). CCB thanks PELD-PIAP/CNPq for support. M.C. was supported by a Ramón y Cajal Fellowship (RYC2020-029829-I) and the Serra Hunter programme (Generalitat de Catalunya). GAG was supported by #DEB-2025982, NTL LTER. PH received financial support from the eLTER PLUS project (Grant Agreement #871128). JMH was supported by the Federal Aid in Sport Fish Restoration Program (F-69-P, Fish Management in Ohio), administered jointly by the United States Fish and Wildlife Service and the Division of Wildlife, Ohio Department of Natural Resources (projects FADR65, FADX09, and FADB02). KLH and RP thank the Oulanka Research Station. MBF thanks over 300 students, staff, and faculty that have participated in the Kentucky Lake Long-Term Monitoring Program at Hancock Biological Station, Murray State University, Murray, KY. MJJ thanks the Northumberland Wildlife Trust for site access. IISD-ELA zooplankton samples were counted and identified primarily by Willy Findlay and Alex Salki. Field collections within IISD-ELA were overseen by Mark Lyng and Ken Sandilands. Funding for most of the IISD-ELA data was provided by Fisheries and Oceans Canada. PP and MS were supported by the Czech Science Foundation (P505-20-17305S). LCR is grateful to the Núcleo de Pesquisas em Limnologia, Ictiologia e Aquicultura (Nupélia) at Universidade Estadual de Maringá for logistic support; CNPq/ PELD for financial support and CNPq for a scholarship. AR was supported by NSF CAREER #2047324 and by UC Berkeley new faculty funds. We thank countless colleagues at all partner institutes for their help with collecting the time series data.

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Preprint: 10.32942/osf.io/mpf5x (DOI)