Data from: Spatial scaling of environmental variables improves species-habitat models of fishes in a small, sand-bed lowland river

Radinger J, Wolter C, Kail J

Date Published: November 20, 2015

DOI: http://dx.doi.org/10.5061/dryad.b6k1k

 

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Title Set_AV: Single boosted regression tree (BRT) habitat models for 13 fish species based on assessed hydromorphological variables without topological variables
Downloaded 24 times
Description Results for single boosted regression tree (BRT) models for 13 fish species, 4 modelled distance classes (0, 200, 2500, 4000 m) and assessed hydromorphological data (AV) without topological variables. Model results include a global BRT model (brt.model.global, including all variables) and a final BRT model (brt.model.final, including only statistically relevant variables) for each species. Furthermore, summarizing statistics (brt.stats.final) for each final model (e.g. cross-validated AUC) and associated plots showing the influence of selected selected variables (species_response.pdf) are provided. Models are stored as R objects in the *.rds format and can be loaded with the R command readRDS().
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Title Set_AV_TV: Single boosted regression tree (BRT) habitat models for 13 fish species based on assessed hydromorphological variables and topological variables
Downloaded 17 times
Description Results for single boosted regression tree (BRT) models for 13 fish species, 4 modelled distance classes (0, 200, 2500, 4000 m) and assessed hydromorphological data (AV) with topological variables (stream orders, distance from mouth). Model results include a global BRT model (brt.model.global, including all variables) and a final BRT model (brt.model.final, including only statistically relevant variables) for each species. Furthermore, summarizing statistics (brt.stats.final) for each final model (e.g. cross-validated AUC) and associated plots showing the influence of selected selected variables (species_response.pdf) are provided. Models are stored as R objects in the *.rds format and can be loaded with the R command readRDS().
Download Set_AV_TV.zip (497.8 Mb)
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Title Set_MV: Single boosted regression tree (BRT) habitat models for 13 fish species based on measured hydromorphological variables without topological variables
Downloaded 20 times
Description Results for single boosted regression tree (BRT) models for 13 fish species, 4 modelled distance classes (0, 200, 2500, 4000 m) and measured hydromorphological data (MV) without topological variables (stream orders, distance from mouth). Model results include a global BRT model (brt.model.global, including all variables) and a final BRT model (brt.model.final, including only statistically relevant variables) for each species. Furthermore, summarizing statistics (brt.stats.final) for each final model (e.g. cross-validated AUC) and associated plots showing the influence of selected selected variables (species_response.pdf) are provided. Models are stored as R objects in the *.rds format and can be loaded with the R command readRDS().
Download Set_MV.zip (545.4 Mb)
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Title Set_MV_TV: Single boosted regression tree (BRT) habitat models for 13 fish species based on measured hydromorphological variables and topological variables
Downloaded 23 times
Description Results for single boosted regression tree (BRT) models for 13 fish species, 4 modelled distance classes (0, 200, 2500, 4000 m) and measured hydromorphological data (MV) with topological variables. Model results include a global BRT model (brt.model.global, including all variables) and a final BRT model (brt.model.final, including only statistically relevant variables) for each species. Furthermore, summarizing statistics (brt.stats.final) for each final model (e.g. cross-validated AUC) and associated plots showing the influence of selected selected variables (species_response.pdf) are provided. Models are stored as R objects in the *.rds format and can be loaded with the R command readRDS().
Download Set_MV_TV.zip (495.8 Mb)
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Title GRASS GIS scripts
Downloaded 17 times
Description GRASS GIS scripts for (i) transforming vector based hydromorphological data into GRASS raster format and (ii) calculating distance based average focal predictors for 4 predefined distance classes (0, 200, 2500, 4000 m) using the GRASS rdfilter add-on.
Download GRASS_GIS_scripts.zip (4.414 Kb)
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Title R scripts
Downloaded 19 times
Description R scripts for (i) calculating the boosted regression tree models (BRT), (ii) analyzing and plotting the model performance based on AUC and (iii) analyzing and plotting the contribution of single variables.
Download R_scripts.zip (13.45 Kb)
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Title Model performance (AUC) - dataframe
Downloaded 11 times
Description R-dataframe storing the model performance (AUC) of the single models for 13 species, four modelled distance classes, assessed vs. measured variables and with/without topological variables. The dataframe is stored as R object in the *.rds format and can be loaded with the R command readRDS().
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Title Variable contribution - dataframe
Downloaded 12 times
Description R-dataframe storing the contribution of single variables for each of the final BRT models. The dataframe is stored as R object in the *.rds format and can be loaded with the R command readRDS().
Download VC.df.rds (90.22 Kb)
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Title Variable contribution rank - dataframe
Downloaded 9 times
Description R-dataframe storing the importance rank of single variables for each of the final BRT models. The dataframe is stored as R object in the *.rds format and can be loaded with the R command readRDS().
Download VC.df.rank.rds (3.941 Mb)
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Title README
Downloaded 13 times
Description README including a description of the results, dataframes and variables.
Download README.txt (4.338 Kb)
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When using this data, please cite the original publication:

Radinger J, Wolter C, Kail J (2015) Spatial scaling of environmental variables improves species-habitat models of fishes in a small, sand-bed lowland river. PLOS ONE 10(11): e0142813. http://dx.doi.org/10.1371/journal.pone.0142813

Additionally, please cite the Dryad data package:

Radinger J, Wolter C, Kail J (2015) Data from: Spatial scaling of environmental variables improves species-habitat models of fishes in a small, sand-bed lowland river. Dryad Digital Repository. http://dx.doi.org/10.5061/dryad.b6k1k
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