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\begin{document}

\title{Snow depth distribution in canopy gaps over heterogeneous forest
structure in the Central Pyrenees}



\author[1]{F. Rojas-Heredia}%
\author[1]{Jesus Revuelto}%
\author[1]{Deschamps-Berger C.}%
\author[1]{Esteban Alonso-González}%
\author[1]{P. Domínguez-Aguilar}%
\author[2]{J. García}%
\author[3]{F. Pérez-Cabello}%
\author[1]{Ignacio Lopez-Moreno}%
\affil[1]{Instituto Pirenaico de Ecologia}%
\affil[2]{University of Valencia}%
\affil[3]{University of Zaragoza}%


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  \date{May 25, 2024}


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\begin{abstract}
This research analyses the snow depth distribution in canopy gaps across
two plots in Central Pyrenees, to improve understanding of snow--forest
and topography interactions. Snow depth maps, forest structure--canopy
gap (FSCG) characteristics and topographic variables were generated by
applying \emph{Structure from Motion} algorithms (SfM) to images
acquired from Unmanned Aerial Vehicles (UAVs). Six flights were
conducted under different snowpack conditions in 2021, 2022 and 2023.
Firstly, the snow depth database was analyzed in terms of the ratio
between the radius of the canopy gap and the maximum height of the
surrounding trees ( \emph{r}/ \emph{h}), in order to classify the gaps
as \emph{small-size}, \emph{medium-size}, \emph{large-size} or
\emph{open areas} at both sites independently. Then the Kendall
correlation coefficients between the snow depth, FSCG and topographic
variables were computed, and a Random Forest (RF) model for each survey
day was implemented, to determine the influence of these variables for
explaining snow depth patterns. The results demonstrate the high
reliability of the UAV SfM photogrammetry approach for measuring
snowpack dynamics at fine scale in canopy gaps and open areas. At site
1, the larger the \emph{r}/ \emph{h} observed, the greater was the snow
depth obtained. This pattern was not evident at site 2, which presented
high variability related to the survey dates and categories,
highlighting the relevance of topography for determining optimum snow
accumulation in forested areas. \emph{Slope} systematically exhibited a
negative and significant correlation with snow depth, and was
consistently the highest-ranked variable for explaining snow
distribution at both sites according to the RF models. \emph{Distance to
the Canopy Edge} also presented high influence, especially at site 1.
The findings suggest differences in the main drivers throughout each
site and survey of the topographic and FSCG variables are needed to
understand snow depth distribution over heterogeneous mountain forest
domains.%
\end{abstract}%



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\textbf{Hosted file}

\verb`SnowDepthDistributionInCanopyGaps_RojasHerediaEtAl_2024.docx`  available at \url{https://authorea.com/users/458935/articles/853078-snow-depth-distribution-in-canopy-gaps-over-heterogeneous-forest-structure-in-the-central-pyrenees}

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