Abstract Understanding the effects of climate on biodiversity and its different levels of response to climatic variation is important for addressing conservation-based questions: the use of bioclimatic variables and species modelling tools is common in environmental, agricultural and biological sciences. Unfortunately, most of the ecological local studies are limited to the use of global data with coarse spatial resolutions, while fine‐grain climate data are necessary to capture environmental variability and perform reliable modelling. We propose a high-resolution dataset (40 m grid) of the suite of original coarse-grain bioclimatic variables proposed by WorldClim 2 for the island of Sardinia (Italy); variations amongst our dataset and WorldClim 2 were calculated and mapped to show the spatial distribution of differences between all pairs of variables. We observed relevant differences for the bioclimatic variables related to rainfall (mean RMSE = 39.79; mean nRMSE = 0.21) compared to the temperature ones (mean RMSE = 4.81; mean nRMSE = 0.11). Moreover, discrepancies are not evenly distributed in the territory: the greater differences correspond to the areas characterized by complex orographic systems. Results recommend caution in making ecological assessments based on bioclimatic variables derived from global data with coarse spatial resolutions in physiographically complex landscapes, especially in the Mediterranean regions, characterized by seasonal climatic variations and high levels of biodiversity and biogeographical complexity. These new data will support a new generation of research studies in a broad array of ecological applications at a much finer scale than previously possible.

中文翻译：

---

支持地中海生物多样性热点生态建模的高空间分辨率生物气候变量

摘要 了解气候对生物多样性的影响及其对气候变化的不同反应水平对于解决基于保护的问题很重要：生物气候变量和物种建模工具的使用在环境、农业和生物科学中很常见。不幸的是，大多数生态局部研究仅限于使用具有粗略空间分辨率的全球数据，而细粒度气候数据对于捕捉环境变化和进行可靠的建模是必要的。我们提出了 WorldClim 2 为撒丁岛（意大利）提出的原始粗粒生物气候变量套件的高分辨率数据集（40 m 网格）；我们计算并映射了我们的数据集和 WorldClim 2 之间的变化，以显示所有变量对之间差异的空间分布。我们观察到与降雨相关的生物气候变量（平均 RMSE = 39.79；平均 nRMSE = 0.21）与温度变量（平均 RMSE = 4.81；平均 nRMSE = 0.11）的相关差异。此外，差异在领土内的分布并不均匀：较大的差异对应于以复杂地形系统为特征的地区。结果表明，在基于来自全球数据的生物气候变量进行生态评估时要谨慎，在地理复杂的景观中，尤其是在地中海地区，尤其是在以季节性气候变化和高度生物多样性和生物地理复杂性为特征的具有粗糙空间分辨率的全球数据中。