ELIA model
ELIA is an energy-information-landscape integrated analysis
resulting from a mathematical model (see 24 for a detailed
methodological description, and Annex B inSupplementary Information ). It combines the landscape
functional structure (L ) with the interlinking pattern of energy
flows driven by farming (E ) and the information carried by them
(I ), as a proxy of the potential biodiversity located in cultural
landscapes. ELIA allows to interrelate the three indicators
(E , I , L ) accounted in a spatial-explicit manner in
each unit of analysis (i.e. transects) of digital land cover maps, to
then relate them with georeferenced biodiversity data (Fig. 4 ).
Agroecosystem’s energy storage (Fig. 5a ) is seen as the
harnessing of dissipation thanks to the farmers’ activity that generates
and increases energy loops (30 ). Farmers’ energy reinvestment
(E ) also means that this energy looping does not occur randomly
across space and time, because it is driven by information (I ).
Depending on the information delivered by farmers, the energy flows are
redistributed in one or another way with different intensities across
the agroecosystem. It is because energy carriers flow across different
land uses following a deliberate pattern that they ‘imprint’ a specific
land cover mosaic (L ) that we recognize as a cultural landscape
(Fig. 5b ). The resulting mathematical model (24 )
allows calculating a three-dimensional relationship among E ,I and L (Fig. 5c ), starting from the interaction
between metabolic fluxes and land-uses which give rise to specific
human-transformed landscapes. It can be expressed combining the
landscape functional structure with the complexity of the interlinking
pattern of energy flows (their ‘loopiness’) and the information carried
by them (49 ), taken as a biodiversity predictor in cultural
landscapes:
\begin{equation}
\text{ELIA}=\left(\frac{\left(EI\right)\text{\ L}}{\max\left\{\text{EI}\right\}a}\right)^{1/3}\nonumber \\
\end{equation}Where E is the energy storage, I is the information
carried by the network of energy flows and L is the energy
‘imprint’ in the landscape functional structure (24 ). Lis measured as the landscape pattern (land-cover heterogeneity) and
improved including the landscape processes (ecological connectivity).
According to the ELIA model,\(\max\left\{\text{EI}\right\}e=0.6169\ \)(Annex B ). Once
we have the maximum \(EI\) to structure the landscape, we can add the
landscape functional structure (L ). ELIA values
theoretically range from 0 to 1.
[Insert Figure 5 here]
The socio-metabolic analysis is based on an energy flow-fund approach of
agroecosystems (50 ) of the BMR, using data from the Spanish
Ministry of Agriculture and the Catalan Statistics Institute
(44 ). The landscape composition and configuration has been
calculated from the 2009 Land Cover Map of Catalonia
(www.creaf.uab.es/mcsc/).