deletions | additions       diff --git a/Discusion.tex b/Discusion.tex  index 4947b53..8488f9e 100644  --- a/Discusion.tex  +++ b/Discusion.tex 
...
\section{Discusion}  Including interactions in ecological studies, for complexity understanding is no easy. For example, it has been tried with global models that including the greatest number of variables, resulting also in serious deficiencies in predictability, especially for the limitation for the incorporation of all interactions ecosystem multi-elements and components (Moore et al. 2002). Alternative forms of explain de complex dynamics have been trying with the assessment of attributes like resilience and robustness (Ulanowicz et al. 2009). Also, ecological complexity has been related with stability. This way, complexity characterization has been supported in variables such as species richness (number of species), connectance (fraction of the possible interspecific interactions), interaction strength (effect of one species’ density on the growth rate of another specie) and evenness (abundance variance). Meanwhile, stability has been related with resilience (velocity to return to the equilibrium), resistance (variable’ grade of change) and variability (population density variance) (Pimm, 1984). However, these interpretations of interactions are conducts to find an explanation of functional complexity, than the evaluation of how complex is an ecosystem. Variables with a more homogeneous distribution will produce more information, yielding higher values of emergence. Variables with a more heterogeneous distribution will produce higher self-organization values.     As it can be seen, using h, periodic or seasonal dynamics can be followed and studied.