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\section{Introduction}       In recent years, the scientic study of complexity in ecological systems has increased the understanding of a broad range of phenomena such as ecological richness, abundance, and hierarchical structure. As result different approximations were explored in focus to develop a mathematical formalism to represent the ecological complexity as ecological indicator (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 (Parro, 2010).  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 In addition there are two important propeties, homeostasis and autopoiesis, which supports the self-regulation and autonomy of the system. The above properties comes  from the relevant interactions interactiona  among components. Interactions system's components and generates novel ingormation. These interactions  determine the future of systems ecosystems  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 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 complexity generation.In addition, ecological systems are supported in two phenomenons related with the     In addition, there are two properties that support the above processes: homeostasis refers to regularity of states in the 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 and taking into account that the balance between change (chaos) and stability (order) states has been proposed as a characteristic of complexity (Langton,**; Kaufmann), we can say that more chaotic systems produce more information (emergence) and more stable systems are more organized. Thus we propose, based on Information Theory, that complexity can be defined as the balance between emergence and self-organization (Gershenson & Fernández; Fernández et. al. 2015). This approach have been applied to ecological systems () with good results indicating that ecological dynamics can be described in terms of information.  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). Formals aspects for homeostasis and autopoiesis can be found in Fernández et al., 2014.  In Considering there are multiple ways to describe  the above context, state of an ecosystem and taking into account that the balance between change (chaos) and stability (order) states has been proposed as a characteristic of complexity (Langton,**; Kaufmann), we can say that more chaotic systems produce more information (emergence) and more stable systems are more organized. Thus  we apply propose, based on information theory, that complexity can be defined as the balance between emergence and self-organization (Gershenson & Fernández; Fernández et. al. 2015). This approach have been applied to some ecological systems (Fernández & Gershenson 2013; Fernández et al. 2013*eccs) with good results indicating that ecological dynamics can be described in terms of information.  This papers expands the useful of the application of complexity measuring applying formal expresions of complexity, self-organization, emergence, homeostasis and autopoiesis to the physiochemical, nutrients and biomass subsystems to four types of lakes located in an latitudinal gradiente (arctic, highland template, lowland template to tropical), in focus to evaluate the usefulness and bennefits in ecological systems.  \cite{cite:0}