GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2020 to 2100 under Diverse SSP-RCP Scenarios

DOI

Understanding the potential impact of climate change on species distributions is crucial for biodiversity conservation and ecosystem management. Rodents, as one of the most diverse and widespread mammalian groups, play a critical role in ecological systems but also pose significant risks to agriculture systems and public health. Here, we present GridScopeRodents, a high-resolution global dataset projecting the distribution of 10 rodent genera from 2020 to 2100 under different Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathway (RCP) scenarios. Using occurrence data from GBIF and environmental variables from WorldClim and other sources, we employ MaxEnt, an ecological niche modeling tool, to estimate occurrence probability at a spatial resolution of 1/12° (~10 km at the equator). The dataset encompasses four SSP-RCP scenarios (SSP126, SSP245, SSP370, SSP585) and 10 global climate models (GCMs), providing projections at 20-year intervals. GridScopeRodents serves as a valuable resource for research on biodiversity conservation, invasive species monitoring, agricultural sustainability, and disease ecology.The GridScopeRodents dataset has a spatial resolution of 1/12°, covering four SSP-RCP scenarios and 10 global climate models (GCMs). It includes projection data at 20-year intervals from 2020 to 2100, as well as baseline data modeled using 1970–2000 records, comprising a total of 9,660 files with a combined size of 335 GB.All data are stored in GeoTIFF (.tif) format and can be accessed and processed using ArcGIS, ENVI, R, and Python. The dataset is organized into two main directories: historical_baseline and future. The historical_baseline folder follows the structure Genus_Statistics, while the future folder is organized as Genus_Statistics_Year_SSP-RCP. Notably, "historical" refers to distribution probabilities modeled using 1970–2000 data, serving as the baseline. Files in the historical_baseline folder follow the naming convention Genus_Statistics.tif, while those in the future folder use the format Genus_GCM_Year_SSP-RCP_Statistics.tif. Here, Genus represents the rodent genus, GCM denotes the global climate model used, Year specifies the projected time period, SSP-RCP indicates the shared socioeconomic pathway and representative concentration pathway, and Statistics describes the file's data characteristics. For example, Akodon_ACCESS-CM2_2021-2040_ssp126_avg.tif represents the average projected occurrence probability for Akodon under the SSP1-RCP2.6 scenario and the ACCESS-CM2 global climate model during 2021–2040 over 25 replicate runs. Each GeoTIFF file contains grid values representing species distribution probabilities for each cell, with outputs transformed using the cloglog function.

Identifier
DOI https://doi.org/10.5522/04/28652219.v1
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Metadata Access https://api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:figshare.com:article/28652219
Provenance
Creator Lan, Yang ORCID logo; Wu, Xiao; Xu, Meng; Li, Keran; Zhou, Guangjin ORCID logo; Huan, Yizhong ORCID logo; Lun, Fei; Shang, Wenlong; Zhang, Riqi ORCID logo; xie, Yang
Publisher University College London UCL
Contributor Figshare
Publication Year 2025
Rights https://creativecommons.org/licenses/by/4.0/
OpenAccess true
Contact researchdatarepository(at)ucl.ac.uk
Representation
Language English
Resource Type Dataset
Discipline Biogeography; Biospheric Sciences; Geosciences; Natural Sciences