index.fff

\begin{figure}

{\centering \includegraphics{figures/conceptual_2.png}

}

\caption{\label{fig-embedding}The embedding process (\textbf{A}) can
help to identify links (interactions) that may have been missed within
the original community (represented by the orange dashed arrows,
\textbf{B}). Transfer learning (\textbf{D}) allows for the prediction of
links (interactions) even when novel species (\textbf{C}) are included
alongside the original community. This is achieved with other
ecologically relevant predictors (\emph{e.g.} traits) in conjunction
with the known interactions to infer latent values (\textbf{E}).
Ultimately this allows us to predict links (interactions) for species
external from the original sample (blue dashed arrows) as well as
missing within sample links (\textbf{F}). Within this context the
predicted (and original) networks as well as the ecological predictors
used (green boxes) are products that can be quantified through
measurements in the field, whereas the embedded as well as imputed
matrices (purple box) are representative of a decomposition of the
interaction matrices onto the embedding space}

\end{figure}
\efloatseparator
 
\begin{figure}[H]

{\centering \includegraphics{index_files/figure-latex/fig-illustration-1-output-1.png}

}

\caption{\label{fig-illustration-1}Validation of an embedding for a
host-parasite metaweb, using Random Dot Product Graphs. \textbf{A},
decrease in approximation error as the number of dimensions in the
subspaces increases. \textbf{B}, increase in cumulative variance
explained as the number of ranks considered increases; in \textbf{A} and
\textbf{B}, the dot represents the point of inflexion in the curve (at
rank 39) estimated using the finite differences method. \textbf{C},
position of hosts and parasites in the space of latent variables on the
first and second dimensions of their respective subspaces (the results
have been clamped to the unit interval). \textbf{D}, predicted
interaction weight from the RDPG based on the status of the species pair
in the metaweb. Source:
\href{https://PoisotLab.github.io/ms_metaweb_perspectives/notebooks/SupplementaryMaterial-preview.html\#cell-fig-illustration-1}{Demonstration
of metaweb embedding using RDPG}}

\end{figure}
\efloatseparator
 
\begin{figure}[H]

{\centering \includegraphics{index_files/figure-latex/fig-illustration-2-output-1.png}

}

\caption{\label{fig-illustration-2}Ecological analysis of an embedding
for a host-parasite metaweb, using Random Dot Product Graphs.
\textbf{A}, relationship between the number of parasites and position
along the first axis of the right-subspace for all hosts, showing that
the embedding captures elements of network structure at the species
scale. \textbf{B}, weak relationship between the body mass of hosts (in
grams) and the position alongside the same dimension. \textbf{C}, weak
relationship between body mass of hosts and parasite richness.
\textbf{D}, distribution of positions alongside the same axis for hosts
grouped by taxonomic family. Source:
\href{https://PoisotLab.github.io/ms_metaweb_perspectives/notebooks/SupplementaryMaterial-preview.html\#cell-fig-illustration-2}{Demonstration
of metaweb embedding using RDPG}}

\end{figure}