Vegetation structure and climate shape mountain arthropod distributions across trophic levels

Arthropods play a vital role in ecosystems, yet their distributions remain poorly understood, particularly in mountainous regions. This study delves into the modeling of the distribution of 31 foliar arthropod genera in the French Alps, using a comprehensive approach encompassing multi-trophic sampling, community DNA metabarcoding, and random forest models. The results underscore the significant importance of vegetation structure, such as herbaceous vegetation density, and forest density and heterogeneity, along with climate, in shaping the distributions of most arthropods. These responses to environmental gradients are consistent across trophic groups, with the exception of nectarivores, whose distributions are more sensitive to landscape structure and water availability. By leveraging community DNA metabarcoding, this study sheds light on the understudied drivers of arthropod distributions, emphasizing the importance of modeling across diverse trophic groups to anticipate arthropod re..., , , # Vegetation structure and climate shape mountain arthropod distributions across trophic levels

\[[https://doi.org/10.5061/dryad.wdbrv15xr](https://doi.org/10.5061/dryad.wdbrv15xr)]

This dataset contains data and script necessary to reproduce all analyses of the manuscript \"*Vegetation structure and climate shape mountain arthropod distributions across trophic levels*\". This study delves into the modeling of the distribution of 31 foliar arthropod genera in the French Alps, using a comprehensive approach encompassing multi-trophic sampling, community DNA metabarcoding, and random forest models.

## Description of the data and file structure

**Data used in the main analyses:**

* ***CO1c.MTROPH.rds***, a 'metabarlist' sensu *metabaR* package, is an R list built of 4 arrays respectively describing reads, motus, PCRs, and sample metadata. With this list, the script *1_Prepare_mblists_for_models_2.R* allows us to obtain the inputs necessary for distribution models and other analyses (e.g...