"Catchment productivity controls local species richness of hyporheic invertebrate communities in tropical New Caledonia streams"
Authors/Creators
- 1. Université Claude Bernard Lyon 1, CNRS, ENTPE, UMR 5023 LEHNA, Villeurbanne, France
- 2. Bio eKo Consultants, Nouméa, New-Caledonia
- 3. INRAE, UR-RiverLY, Centre Lyon-Grenoble Auvergne-Rhône-Alpes,Villeurbanne, France
- 4. Stuttgart State Museum of Natural History, Stuttgart, Germany
- 5. University of Greifswald, Zoological Institute and Museum, Greifswald, Germany
- 6. Department of Life, Health and Environmental Sciences, University of L'Aquila, Italy
- 7. Institut Universitaire de France, Paris, France
Description
This dataset allows to reproduce the statistical analysis whose results are presented in the article:
"Catchment productivity controls local species richness of hyporheic invertebrate communities in tropical New Caledonia streams"
In all tables, the 228 freshwater hyporheic sites are identified by a code ("Site_Code") and coordinates in decimal degrees WGS 84 ("X_long","Y_lat").
- File "Env_predictors_response_variables_Mouron_et_al_2025.csv" : main dataset with abundance, observed richness and estimated richness at a sample coverage level of 95% for total community, fast-growing species and slow-growing species, together with local and catchment predictors.
The nine local predictors describe in-stream habitat conditions : dissolved oxygen ("DO", mg/L), redox potential ("Redox_potential", mV), pH ("pH"), specific conductance("Sp_conductance", µS/cm), temperature of hyporheic water ("Temperature", degree Celsius), mean annual air temperature ("Mean_annual_temp", degree Celsius), river width ("River_width", m), elevation ("Elevation", m), stream slope ("Stream_slope", m/m).
The nine catchments predictors describe the entire upstream contributing catchment : catchment area ("Catchment_area", km2), areal proportion of peridotite ("Peridotite", %), normalized difference vegetation index ("NDVI"), three land cover predictors ("Landcover1", "Landcover2", "Landcover3"), mean annual precipitation ("Precipitation", mm/year), low flow specific discharge ("Discharge", L/s/km2), areal proportion of surfaces eroded by mining activities ("Mining").
Column headings for abundance and species richness data are as follows.
“Abundance_Surf”: abundance of fast-growing species; “Abundance_GW”: abundance of slow-growing species; “Total_abundance”: total abundance; “Richness_Surf”: observed richness for the fast-growing species; “Richness_GW”: observed richness for the slow-growing species; “Total_Richness”: observed richness for the total community; “qD_Surf”: estimated richness (at a sample coverage level of 95%) for the fast-growing species; “qD_Surf_rd”: rounded value of estimated richness for the fast-growing species; “qD_GW”: estimated richness for the slow-growing species; “qD_GW_rd”: rounded value of estimated richness for the slow-growing species; “qD_Tot”: estimated richness for the total community; “qD_Tot_rd”: rounded value of estimated richness for the total community.
- File "Sample_species_data_Mouron_et_al_2025.csv": species per site data. OTU: operational taxonomic unit; MOTU: molecular operational taxonomic unit.
- File R_Script_Mouron_et_al_2025.rmd : R Markdown document to open in RStudio, containing the script used to reproduce the statistical analysis in R.
- File AED.R : R script from Zuur et al. 2009 used to compute variance inflation factors (VIFs) (Zuur AF, Ieno EN, Walker N, et al (2009) Mixed effects models and extensions in ecology with R. Springer New York, New York, NY)
Files
Env_predictors_response_variables_Mouron_et_al_2025.csv
Files
(341.0 kB)
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