Species traits and vulnerability scores: global marine fauna

Updated datasets from Butt et al. (2022). A trait-based framework for assessing the vulnerability of marine species to human impacts. Ecosphere, 13(2), e3919. https://doi.org/10.1002/ecs2.3919. These data are generated from scripts in https://github.com/mapping-marine-spp-vuln/spp_vuln_framework, updated since the original publication. These files contain trait information for 47 different traits (with categorical values) across 54,718 marine faunal species. These traits were then used to calculate vulnerability scores for species vulnerability to 23 different anthropogenic stressors. Species/trait data are contained in normalized relational tables: * spp_traits_junction.csv (trait probability for species-trait pairs; keys for species, trait values, gapfill levels) * spp_traits_taxa_lookup.csv (WoRMS Aphia ID, sci name, taxon) * spp_traits_trait_val_lookup.csv (trait/value pairs with key) * spp_traits_gapfill_levels.csv (taxonomic ranks at which trait values were matched or gapfilled - see Butt et al. 2022 for details). Species/vulnearbility data are contained in normalized relational tables: * spp_vuln_junction.csv (vulnerability scores and components for species-stressor pairs; keys for species and stressors) * spp_vuln_taxa_lookup.csv (WoRMS Aphia ID, scientific name, taxon) * spp_vuln_stressor_lookup.csv (stressor/ID pairs) Each .zip also contains a readme with R code to show how to join tables easily.