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\title[Wetland model]{Spatio-temporal dynamic modeling of plant communities responses to hydrological pressures in a semiarid Mediterranean wetland}
\author[ISEM 2013]{J. Mart{\'i}nez-L{\'o}pez$^{1}$, J. Mart{\'i}nez-Fern{\'a}ndez$^{1,2}$, B. Naimi$^{3}$, M.F. Carre{\~n}o$^{1}$ and M.A. Esteve$^{1}$}

\date{\scriptsize $^{1}$Ecology and Hydrology Department - University of Murcia (Murcia, Spain)\\$^{2}$Applied Biology Dept. University Miguel Hernandez (Elche, Spain)\\$^{3}$ITC - University of Twente (Enschede, The Netherlands)}


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\begin{document}

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\frame{\maketitle
\begin{center}
\includegraphics[width=75mm]{figures/bandeau_conf.png}
\end{center}
}

\section{Introduction}

\frame{\frametitle{Study area}
\begin{center}
\includegraphics[width=0.9\textwidth]{figures/fig1.png}
\end{center}
}

\frame{\frametitle{Marina del Carmoli wetland (300 ha)}
\begin{center}
\includegraphics[width=\textwidth]{figures/cr10.png}
\end{center}
}

\frame{\frametitle{Wetland plant communities}
\begin{block}{}
Semiarid Mediterranean saline wetlands are semi-terrestrial ecosystems
\end{block}
\begin{center}
\includegraphics[width=\textwidth]{figures/mc_ila_pcoms.png}
\end{center}
\begin{exampleblock}{}
\begin{itemize}
\item Salt steppe (left) - priority habitat by the Habitats Directive
\item Salt marsh (center) - habitat of interest by the HD
\item Reed beds (right) ({\it Phragmites australis}) - invasive
\end{itemize}
\end{exampleblock}
}

\frame{\frametitle{External water inputs}
Percentage of irrigated areas has increased in the last decades due to the opening of a water transfer (Mart\'inez-L\'opez et al., 2013)
\begin{center}
\includegraphics[width=\textwidth]{figures/cr10_ws_lulc.png}
\end{center}
}

\frame{\frametitle{Plant communities change}
\begin{alertblock}{}
Important plant communities are being lost!
\end{alertblock}
\begin{center}
\includegraphics[width=0.7\textwidth]{figures/vegmaps_mc.png}
\\
Carre\~no et al., 2008; Mart\'inez-L\'opez et al., 2012
\end{center}
}

%\section{Objectives}

\frame{\frametitle{Objective}
\begin{block}{}
\begin{itemize}
\item Spatially explicit wetland model of how irrigated agriculture is affecting plant community composition in this semiarid Mediterranean wetland
%\begin{itemize}
%\item tool for wetland conservation and management studies
%\item forecast the loss of important plant communities due to irrigation pressures
%\end{itemize}
\end{itemize}
\end{block}
}

\section{Methods}

\frame{\frametitle{Modelling environment}
\begin{block}{}
\begin{itemize}
\item R as a modelling environment:
\begin{itemize}
\item GIS capabilities
\item source code is flexible
\item free availabity and growing user community
\end{itemize}
\end{itemize}
\end{block}
\begin{center}
\includegraphics[width=0.25\textwidth]{figures/Rlogo.png}
\end{center}
}

\frame{\frametitle{State variables}
\begin{exampleblock}{}
\begin{itemize}
\item Wetland is divided into pixels (25 m)
\item Plant communities are modelled separately pixel by pixel (4 maps)
\item The total abundance of plant communities within a pixel is limited so:
\begin{itemize}
\item competition among plant communities mediated by
\begin{itemize}
\item total drainge water input to the wetland
\item spatial environmental variables influencing water availability and growth
\end{itemize}
\item the dispersion of other PC from the surrounding pixels
\end{itemize}
\end{itemize}
\end{exampleblock}
\begin{center}
\includegraphics[width=0.5\textwidth]{figures/pixel.png}
\end{center}
}

\frame{\frametitle{Initial and validation maps of plant communities}
\begin{exampleblock}{}
Model was tested by means of remote sensing data for the period 1992-2008
\end{exampleblock}
\begin{center}
\includegraphics[width=0.7\textwidth]{figures/vegmaps_mc.png}
\\
Carre\~no et al., 2008; Mart\'inez-L\'opez et al., 2012
\end{center}
}

%\frame{\frametitle{Main variables and parameters}
%\begin{exampleblock}{}
%Flow from state variable A to B (per pixel)
%\end{exampleblock}
%\centering
%\includegraphics[width=\textwidth]{figures/mcdynmod1.png}
%\begin{alertblock}{}
%Shaded squares represent non spatial variables/parameters and oval shaped variables refer to state variables.
%\end{alertblock}
%}

\frame{\frametitle{Model assumptions I}
\begin{exampleblock}{}
\begin{itemize}
\item Increasing water input
\item Only conversion to more humid / less saline plant communities
\end{itemize}
\end{exampleblock}
\begin{center}
\includegraphics[width=0.8\textwidth]{figures/mc_ila_pcoms.png}\\
\includegraphics[width=0.7\textwidth]{figures/growth.png}
\end{center}
}

\frame{\frametitle{Model assumptions II}
\begin{exampleblock}{native vs. invasive taxa}
\begin{itemize}
\item invasive reed beds are potentially present in all pixels
\item salt marsh is able to disperse into neighbour pixels
\end{itemize}
\end{exampleblock}
\begin{center}
\includegraphics[width=0.3\textwidth]{figures/expansion2.png} \hspace{5mm}
\includegraphics[width=0.5\textwidth]{figures/neighborhood3.png}
\end{center}
}

\frame{\frametitle{Non spatial forcing input}
\begin{exampleblock}{Drainage water input}
WARP index (Mart\'inez-L\'opez et al., 2014a,b)
\end{exampleblock}
\begin{center}
\includegraphics[width=0.6\textwidth]{figures/mc_ila_warp_time.png}
\end{center}
}

\frame{\frametitle{Wetland environmental spatial parameters}
\begin{exampleblock}{}
\begin{itemize}
\item (A) distance map to ephemeral river 1 ({\bf reed beds})
\item (B) distance map to ephemeral river 2 ({\bf reed beds})
\item (C) Flow accumulation map ({\bf salt marsh})
\end{itemize}
\end{exampleblock}
\includegraphics[angle=-90,width=\textwidth]{figures/env_spat_var.png}
\begin{alertblock}{}
\begin{itemize}
\item All parameters are on a relative 0--1 scale.
%\item Map algebra operations were performed using GRASS GIS and imported into R using the 'rgdal' and 'raster' libraries.
\end{itemize}
\end{alertblock}
}

\frame{\frametitle{Model diagram}
\begin{center}
\includegraphics[width=\textwidth]{figures/mcdynmod3.png}
\end{center}
}

\frame{\frametitle{Model development/execution}
\begin{block}{}
\begin{enumerate}
\item Initial dynamic model was developed using Stella (1 pixel)
\item Conversion to R using 'StellaR' script (Naimi and Voinov, 2012)
\item State variables and spatial environmental variables as matrices
\item Model wrapped as a R function
\item ode.2D("euler" method, time = 24 year, TS = 0.25) {\small (library "deSolve")}
\end{enumerate}
\end{block}
%\begin{center}
%\includegraphics[width=0.5\textwidth]{figures/neighborhood2.png}
%\end{center}
}

%\section{Results}

%\frame{\frametitle{}
%Overall Accuracy: 54\% -- 71\%
%\begin{center}
%\includegraphics[angle=-90,width=0.34\textwidth]{figures/rstack_compar.png}
%\end{center}
%}

%\frame{\frametitle{Simulated total area of each plant community}
%\centering
%\includegraphics[width=0.6\textwidth]{figures/val_all_areas.png}
%\begin{alertblock}{}
%Dots represent the are occupied by each plant community based on RS data and model simulated values are represented by lines
%\end{alertblock}
%}

%\frame{\frametitle{0D Error and similarity measures}
%\begin{center}
%\begin{tabular}{lccc}
%{\bf Plant community} & {\bf r} & {\bf NRMSE (\%)} & {\bf EF} \\ 
%Salt steppe & 0.91 & 44 & 0.77 \\ % 0.01124
%Salt marsh & 0.84 & 54 & 0.65 \\ %0.03817
%Reed beds & 0.88 & 53 & 0.65 \\ % 0.02124
%\end{tabular}
%\end{center}
%\begin{alertblock}{}
%\begin{itemize}
%\item 'r' corresponds to the Pearson correlation coefficient ($P < 0.05$)
%\item 'NMRSE' to the normalized root mean squared error
%\item 'EF' to the efficiency factor.
%\end{itemize}
%\end{alertblock}
%}

\section{Conclusions}

\frame{\frametitle{Conclusions}
\begin{block}{}
\begin{enumerate}
\item The model serves as a tool for
\begin{itemize}
\item wetland conservation and management studies (habitat loss)
\item testing plant community interactions
\item testing relationships between plant communities and environmental variables in space and time
\end{itemize}
\item The library undergoes further developments in order to become a flexible tool for the development of new spatio-dynamic models
\end{enumerate}
\end{block}
}

\end{document}

