StoichLife: A global dataset of plant and animal elemental content

The elemental content of life is a key trait shaping ecology and evolution, yet organismal stoichiometry has largely been studied on a case-by-case basis. This limitation has hindered our ability to identify broad patterns and mechanisms across taxa and ecosystems. To address this, we present StoichLife, a global dataset of 28,049 records from 5,876 species spanning terrestrial, freshwater, and marine realms. Compiled from published and unpublished sources, StoichLife documents elemental content and stoichiometric ratios (%C, %N, %P, C:N, C:P, and N:P) for individual plants and animals. The dataset is standardized and, where available, includes information on taxonomy, habitat, body mass (for animals), geography, and environmental conditions such as temperature, solar radiation, and nutrient availability. By providing an unprecedented breadth of organismal stoichiometry, StoichLife enables the exploration of global patterns, ecological and evolutionary drivers, and context-dependent var..., , , # StoichLife: A global dataset of plant and animal elemental content

[https://doi.org/10.5061/dryad.3tx95x6r2](https://doi.org/10.5061/dryad.3tx95x6r2)

## Description of the data and file structure

*Data compilation*

We developed the StoichLife template structure, which contains data about elemental content and their ratios (%C, %N, %P, C: N, C:P, and N:P) alongside body size measurements, and information regarding sampling locality, country, and taxonomic affiliation (i.e., phylum, class, order, family, species or morphospecies). This template was disseminated among prospective data contributors actively sampling and analyzing plant and animal elemental content across diverse regions worldwide (between 2014 and 2022). In our endeavor, we engaged 24 researchers who contributed datasets on animals (both invertebrates and vertebrates), resulting in 50 datasets, among which some were already published (15 datasets and one dataset from two sources). Additionally, we incorporated dataset...