Lan Yang, Wu Xiao, Xu Meng, Li Keran, Huan Yizhong, Zhou Guangjin, Lun Fei, Shang Wenlong, Zhang Riqi, Xie Yang
School of Economics and Management, Beihang University, Beijing, 100191, China.
College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.
Sci Data. 2025 Aug 22;12(1):1467. doi: 10.1038/s41597-025-05793-0.
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.
了解气候变化对物种分布的潜在影响对于生物多样性保护和生态系统管理至关重要。啮齿动物作为最多样化和分布最广泛的哺乳动物群体之一,在生态系统中发挥着关键作用,但也对农业系统和公共卫生构成重大风险。在此,我们展示了GridScopeRodents,这是一个高分辨率的全球数据集,预测了在四种基于CMIP6的共享社会经济路径-代表性浓度路径(SSP-RCP)情景组合下,10个啮齿动物属在2021年至2100年的分布情况。利用出现数据和环境变量,我们在物种分布建模(SDM)框架内采用最大熵(MaxEnt)算法,以1/12°(约10公里)的空间分辨率估计出现概率。该数据集涵盖四种SSP-RCP情景(SSP126、SSP245、SSP370、SSP585)和10个全球气候模型(GCM),以20年为间隔提供预测。GridScopeRodents是生物多样性保护、入侵物种监测、农业可持续性和疾病生态学研究的宝贵资源。该数据集以GeoTIFF格式公开提供,可通过Figshare访问。