High spatial resolution bioclimatic variables to support ecological modelling in a Mediterranean biodiversity hotspot.

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.