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\begin{document}

\title{Blessing and curse of BioClim variables: A comparison of different
calculation schemes and datasets for species distribution modeling
within the extended Mediterranean area}



\author[1]{Christian Merkenschlager}%
\author[2]{Freddy Bangelesa}%
\author[2]{Heiko Paeth}%
\author[1]{Elke Hertig}%
\affil[1]{University of Augsburg}%
\affil[2]{University of Wuerzburg}%


\vspace{-1em}



  
  \date{May 22, 2024}


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\begin{abstract}
Bioclimatic variables (BCVs) are the most widely used predictors within
the field of ecological niche modeling. However, recent studies indicate
that BCVs alone are not sufficient to describe these limits and more
(bio)climatological variables should be considered. Unfortunately, the
most popular database WorldClim offers only a limited selection of
predictors; thus, other gridded station-based observations or reanalysis
(GSOR) datasets should be taken into account. In the present study, we
investigate how well the BCVs are represented by different GSOR datasets
for the extended Mediterranean area within the period 1970-2020, how
deviations among the datasets differ regionally and how different
calculation schemes affect the representation of BCVs. We consider
different calculation schemes for quarters/months, the annual mean
temperature and the maximum temperature of the warmest month and show
the effects on the respective BCV. Differences resulting from different
calculation schemes are presented for ERA5-Land. Selected BCVs are
analyzed to show differences between WorldClim, ERA5-Land, E-OBS and
CRU. Our results show that (a) deviations between the two calculation
schemes for annual mean temperature (maximum temperature of the warmest
month) diminish (increase) when the temporal resolution is decreased;
(b) with respect to the definition of the respective month/quarter,
temporal shifts can have substantially different effects on the BCVs,
depending on region; (c) overall, all datasets represent the different
BCVs similarly, but with partly large differences in some subregions;
(d) the largest differences occur when specific month/quarters are
defined by the seasonal cycle of precipitation. In summary, (a) since
the definition of BCVs matches different calculation schemes, a
transparent communication of the BCVs calculation schemes is inevitable;
(b) the calculation, integration or elimination of BCVs has to be
examined carefully for each dataset, region, period or species; (c) the
GSOR-Data provide, except some subregions, a consistent representation
of BCVs within the extended Mediterranean region.%
\end{abstract}%



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