deletions | additions       diff --git a/Discusion.tex b/Discusion.tex  index 8488f9e..8bf53b8 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 proposed measures characterize  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 different configurations  and components (Moore et al. 2002). Alternative forms dynamics that elements  ofexplain de  complex dynamics have been trying with systems acquire through their interactions. That means, these measures capture  the assessment of attributes like resilience properties  and robustness (Ulanowicz et al. 2009). Also, ecological complexity has been related tendencies of a system, that is why the scale at which they are described is appropriate.   They will not indicate which element interacted  with stability. This way, complexity characterization has been supported which element, how and when. If we are interested  invariables such as species richness (number of species), connectance (fraction of  the possible interspecific interactions), interaction strength (effect properties and tendencies  ofone species’ density on  the growth rate of another specie) elements, we can change scale  and evenness (abundance variance). Meanwhile, stability has been related with resilience (velocity to return apply the measures there. Still, we have  to be aware that  the equilibrium), resistance (variable’ grade of change) and variability (population density variance) (Pimm, 1984). However, these interpretations of interactions measures  are conducts to find an explanation of functional complexity, than averaging—and thus simplifying—the phenomena they describe. Whether relevant information is lost on  the evaluation averaging depends not only on the phenomenon, but on what kind  of how complex is an ecosystem. information we are.  Variables On the above context, measuring complextiy at ecological systems is very useful due to Including interactions in ecological studies, for complexity understanding has been no easy. For example, it has been tried  with a more homogeneous distribution will produce more information, yielding higher values of emergence. Variables 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 a more heterogeneous distribution will produce higher self-organization values. 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.  As it can be seen, using h, periodic or seasonal dynamics can be followed and studied.