Data and code for: A global dataset of non-native distributions and traits for disease-vector mosquitoes
This deposit contains two taxonomically integrated, harmonized and complementary datasets covering 184 mosquito species of public health relevance. These datasets are designed to support cross-region comparisons, invasion and disease risk assessments, and reproducible research in ecology, biogeography, and public health. Included files: 1. Pabst2026_Introduction_Data.xlsx Non-native mosquito species introduction records. List of the included vector species and list of world regions used to standardize data collection. The introduction records include information the year of first record, establishment status (e.g., established, eradicated, or introduced but not established), and pathways of introduction. 2. Pabst2026_Traits.xlsx Species level trait dataset for 184 vector mosquito species containing 20 unique traits encoded as 46 variables describing ecological, life-history, and macroecological characteristics. 3. Pabst2026_Script.zip Scripted workflow for extracting and summarizing climate variables based on species occurrence.
Authors
- Carla Alexandra Sousa (ORCID: https://orcid.org/0000-0002-2386-7577)
- Rebecca Pabst (ORCID: https://orcid.org/0000-0002-6132-0572)
- César Capinha (ORCID: https://orcid.org/0000-0002-0666-9755)
- Steffen Knoblauch (ORCID: https://orcid.org/0000-0003-3077-8094)
- A. Marler
Institutions
- University of Lisbon (PT)
- University of Colorado Boulder (US)
- Heidelberg University (DE)
- University of Colorado System (US)
- Zoological Research Museum Alexander Koenig (DE)
- Universidade Nova de Lisboa (PT)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-02-18
- DOI
- https://doi.org/10.5281/zenodo.18682212
- Primary Topic
- Mosquito-borne diseases and control
- Type
- article
- Field-Weighted Citation Impact
- 0.00