Code from: Scrutinizing the Wallacean shortfall: Global gaps in snake occurrence data across space and environment

Occurrence records are fundamental for ecological and evolutionary research, providing key information on species’ geographic ranges. However, these records are often taxonomically, spatially, and temporally biased, requiring caution in their use. Here, we analysed the spatial coverage of occurrence records for over 3,500 snake species worldwide to identify geographical gaps, biases, and priority areas for surveys. To do this, we first compiled occurrence records for all continental snake species worldwide and assigned them to an equal-area grid. Recognizing that biogeographic realms differ in evolutionary histories, environmental conditions, and sampling efforts, we conducted all analyses separately for each realm. Using this global dataset, we then calculated inventory completeness metrics to identify well-sampled grid cells. We then used high-resolution climate data to describe the environmental space of each realm and evaluate the extent to which its climatic gradients are repr..., The list of accepted snakes and all their synonyms was used to search for occurrence records in the Global Biodiversity Information Facility. The inventory completeness analysis was performed for all grid cells of 110 x 110 km and, for each biogeographic realm, the well-sampled cells were selected based on four parameters: slope, number of records, completeness, and record-to-richness ratio. After that, the 19 bioclimatic variables were downloaded and cropped for each realm. To reduce the dimensionality of bioclimatic variables and synthetically describe the environmental space, we performed a Principal Component Analysis (PCA) for each terrestrial realm. The first and second principal components were used to represent the variation in the bioclimatic variables within each realm. For each biogeographic realm, we quantified the number of climate types and the proportion of these that are covered by well-sampled cells. To define the number of climatic types, we classif..., # Code from: Scrutinizing the Wallacean shortfall: Global gaps in snake occurrence data across space and environment

This repository contains the code necessary to perform the analyses presented in the paper '**Scrutinizing the Wallacean shortfall: Global gaps in snake occurrence data across space and environment**'

**well_sampled_1.csv:** This file contains the well-sampled cells identified through the Inventory completeness analyses for the Nearctic, Western Palearctic, and Australasia realms.

* id: Identifier of the well-sampled grid cell.
* Longitude: Longitude of the well-sampled grid cell in decimal degrees.
* Latitude: Latitude of the well-sampled grid cell in decimal degrees.
* Realm: Biogeographic realm in which the well-sampled grid cell is located.

**well_sampled_2.csv:** This file contains the well-sampled cells identified through the Inventory completeness analyses for the Neotropical, Afrotropical, Eastern Palearctic, and Indomalayan realms.

* id: Identifier of the we..., ,