GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios

<p dir="ltr">This dataset has been published in <i>Scientific Data</i>. If you need to cite the data or learn more about how it was generated, please refer to the paper in <i>Scientific Data</i>: Lan, Y., et al. High-resolution global distribution projections of 10 rodent genera under diverse SSP–RCP scenarios, 2021–2100. <i>Sci Data</i> <b>12</b>, 1467 (2025). <a href="https://doi.org/10.1038/s41597-025-05793-0" rel="noreferrer nofollow noopener" target="_blank">https://doi.org/10.1038/s41597-025-05793-0</a></p><p dir="ltr">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 2021 to 2100 under four CMIP6-based Shared Socioeconomic Pathway–Representative Concentration Pathway (SSP–RCP) scenario combinations. Using occurrence data and environmental variable, we employ the Maximum Entropy (MaxEnt) algorithm within the species distribution modeling (SDM) framework to estimate occurrence probability at a spatial resolution of 1/12° (~10 km). 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 dataset is publicly available in GeoTIFF format and can be accessed via Figshare.</p><p dir="ltr">The <i>GridScopeRodents</i> dataset has a spatial resolution of 1/12° and uses the WGS 1984 coordinate reference system (EPSG:4326), covering 10 genera projections in historical four SSP–RCP scenarios and 10 global climate models (GCMs). It includes projection data at 20-year intervals from 2021 to 2100, as well as baseline data modeled using 1970–2000 records, comprising a total of 9,820 files with a combined size of 340 GB. In addition, a detailed summary of each genus’s ecological and economic relevance, with supporting literature, is provided in a supplementary table titled <i>Rodent Genus Selection Justification (Literature)</i>. The dataset is publicly available via Figshare for Institutions (UCL).</p><p dir="ltr">All data are stored in GeoTIFF (.tif) format and can be accessed and processed using ArcGIS, ENVI, R, and Python. Each GeoTIFF file contains grid-based predictions of habitat suitability, with values ranging from 0 to 1. These values represent the probability of species presence at each grid cell, transformed using the cloglog output function in MaxEnt, which is approximately interpretable as the probability of occurrence under typical presence-only assumptions. A higher value indicates greater predicted environmental suitability for the species, while lower values suggest unsuitable or marginal areas. Users may interpret the continuous output directly, or apply threshold values (e.g., MTSS, ETSS) to convert the suitability layer into a binary presence/absence map. </p><p dir="ltr">The dataset is organized into two main directories: <i>historical_baseline</i> and <i>future</i>. The <i>historical_baseline</i> folder follows the structure <i>Genus_Statistics</i>, while the <i>future</i> folder is organized as <i>Genus_Statistics_Year_SSP-RCP</i>. Notably, “historical” refers to distribution probabilities modeled using 1970–2000 data, serving as the baseline. Files in the <i>historical_baseline</i> folder follow the naming convention <i>Genus_Statistics.tif</i>, while those in the <i>future</i> folder use the format <i>Genus_GCM_Year_SSP-RCP_Statistics.tif</i>. Here, <i>Genus</i> represents the rodent genus, <i>GCM</i> denotes the global climate model used, <i>Year</i> specifies the projected time period, <i>SSP-RCP</i> indicates the shared socioeconomic pathway and representative concentration pathway, and <i>Statistics</i> describes the file’s data characteristics. For example, <i>Akodon_ACCESS-CM2_2021–2040_ssp126_avg.tif</i> represents the average projected occurrence probability for <i>Akodon</i> under the SSP1–RCP2.6 scenario and the ACCESS-CM2 global climate model during 2021–2040 over 25 replicate runs. To enhance the applicability of the results and reduce uncertainty arising from inter-model variability, we additionally provide ensemble-mean projections averaged across the ten global climate models (GCMs). These ensemble data products cover all SSP–RCP scenarios and future time slices (2030s, 2050s, 2070s, and 2090s). The ensemble-mean maps of each genus are stored in the <i>GCM_Averaged_Projections</i> subfolder within the <i>future</i> directory of the Figshare dataset named <i>Genus_Year_SSP-RCP_GCM_Averaged.tif</i>. Users seeking more generalized or policy-relevant distribution trends may find these averaged outputs preferable to projections from individual GCMs.</p>