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In recent years, the scientic study of complexity in ecological systems, systems  has increased the understanding of a broad range of phenomena, phenomena  such as diversity, ecological richness,  abundance, and hierarchical structure. As result different approximations are developed were explored in focus  to find develop  a formal measure mathematical formalism  to represent the ecological complexity as ecological indicator (Parrot). (Parrot, 2005).  The advantage of an complexity indicator in ecostytems is the posibility of relation with ecological integrity, diversity and/or resilience, for example. Relation with the spatial and temporal scales, with the structure and function as well are desired (Parrot). (Parro, 2010).  Information Theory In spite of the valuable efforts in ecological modeling over the last decade to take into account the ecological interactions in much detail (Petrovskii and Petrovskay, 2012), more explorations are requiered to explain ecological dynamics in terms of complexity. A start point for complexity studies is considering that ecological systems exhibit properties like emergence, self-organization, and life. Lake dynamics generate novel information from the relevant interactions among components. Interactions determine the future of systems and its complex behavior. Novel information limits predictability,  as it is not included in initial or boundary conditions. It can be said that this novel information is emergent since it is not in  the base components, but produced by their interactions. Interactions can also be used by components to self-organize, i.e. produce a global pattern from local dynamics. Interactions are one the most important reason  for EC formulation. complexity generation. In addition, ecological systems are supported in two phenomenons related with the  In spite of the valuable efforts carried out in order to understanding, clarigy and measuring complexity in ecological systemas, more explorations addition, there  are requiered. Boarding complexity aspects in ecology, it is important to consider that ecological systems exhibit two  propertieslike emergence, self-organization, and life. Lake dynamics generate novel information from the relevant interactions among components. Interactions determine the future of systems and its complex behavior. Novel information limits predictability, as it is not included in initial or boundary conditions. It can be said  that this novel information is emergent since it is not in support  the components, but produced by their interactions. Interactions can also be used by components above processes: homeostasis refers  to self-organize, i.e. produce a global pattern from local dynamics. Interactions are one regularity of states in  the most important reason for complexity generation. system and autopoiesis that reflects autonomy.  To support the formal description of complexity, self-organization and emergence information theory (Shannon, 19499) has been used in different ways, as it can see in Prokopenko et al (2009).  Considering that there are multiple ways to describe the state of an ecosystem, in particular ecosystem and taking into account that  the balance between change (chaos) and stability (order) states has been proposed as a characteristic of complexity. Based on Information Theory, complexity (Langton,**; Kaufmann),  we can say that more chaotic systems produce more information (emergence) and more stable systems are more organized; thus organized. Thus we propose, based on Information Theory, that  complexity can be defined as the balance between emergence and self-organization. In addition, there are two properties that support the above processes: homeostasis refers self-organization (Gershenson & Fernández; Fernández et. al. 2015). This approach have been applied  to regularity of states ecological systems () with good results indicating that ecological dynamics can be described  in terms of information.         In  the system and autopoiesis that reflects autonomy. above context, we apply