01617nas a2200253   4500008004100000022001400041245006100055210006000116300001000176490000600186520088300192653001801075653001501093653002401108653001501132100002001147700003001167700002301197700002601220700002201246700002701268700002901295856003901324       2020                        eng d  a2167-835900aEcosystem antifragility: beyond integrity and resilience0 aEcosystem antifragility beyond integrity and resilience  ae85330 v83 aWe review the concept of ecosystem resilience in its relation to ecosystem integrity from an information theory approach. We summarize the literature on the subject identifying three main narratives: ecosystem properties that enable them to be more resilient; ecosystem response to perturbations; and complexity. We also include original ideas with theoretical and quantitative developments with application examples. The main contribution is a new way to rethink resilience, that is mathematically formal and easy to evaluate heuristically in real-world applications: ecosystem antifragility. An ecosystem is antifragile if it benefits from environmental variability. Antifragility therefore goes beyond robustness or resilience because while resilient/robust systems are merely perturbation-resistant, antifragile structures not only withstand stress but also benefit from it.10aAntifragility10aComplexity10aEcosystem integrity10aResilience1 aEquihua, Miguel1 aAldama, Mariana, Espinosa1 aGershenson, Carlos1 aLópez-Corona, Oliver1 aMunguía, Mariana1 aPérez-Maqueo, Octavio1 aRamírez-Carrillo, Elvia  uhttps://doi.org/10.7717/peerj.853303133nas a2200253   4500008004100000020001400041245005000055210005000105260000600155300001100161490000700172520244900179653001602628653001802644653001402662653001602676653002302692653002202715100002302737700001902760700002602779700002302805856005102828       2017                        eng d  a1476-945X00aComplexity of lakes in a latitudinal gradient0 aComplexity of lakes in a latitudinal gradient  c9  a1–200 v313 aMeasuring complexity is fast becoming a key instrument to compare different ecosystems at various scales in ecology. To date there has been little agreement on how to properly describe complexity in terms of ecology. In this regard, this manuscript assesses the significance of using a set of proposed measures based on information theory. These measures are as follows: emergence, self-organization, complexity, homeostasis and autopoiesis. A combination of quantitative and qualitative approaches was used in the data analysis with the aim to apply these proposed measures. This study systematically reviews the data previously collected and generated by a model carried out on four aquatic ecosystems located between the Arctic region and the tropical zone. Thus, this research discusses the case of exploring a high level of self-organization in terms of movement, distribution, and quality of water between the northern temperate zone and the tropics. Moreover, it was assessed the significance of the presence of a complex variable (pH) in the middle of the latitudinal transect. Similarly, this study explores the relationship between self-organization and limiting nutrients (nitrogen, phosphorus and silicates). Furthermore, the importance of how a biomass subsystem is affected by seasonal variations is highlighted in this manuscript. This case study seeks to examine the changing nature of how seasonality affects the complexity dynamics of photosynthetic taxa (lakes located in northern temperate zone) at high latitudes, and it also investigates how a high level of self-organization at the tropical zone can lead to increase the amount of planktonic and benthic fish which determines the dynamics of complexity. This research also compares the emerging role of how a biomass subsystem has a highest temporal dynamics compared to he limiting nutrients' subsystem. In the same way, the results associated to autopoiesis reflect a moderate degree of autonomy of photosynthetic biomass. It is also discussed the case of how complexity values change in the middle of the latitudinal gradient for all components. Finally, a comparison with Tsallis information was carried out in order to determine that these proposed measures are more suitable due to they are independent of any other parameter. Thus, this approach considers some elements closely related to information theory which determine and better describe ecological dynamics.10aAutopoiesis10aBiocomplexity10aEmergence10aHomeostasis10aInformation theory10aSelf-organization1 aFernández, Nelson1 aAguilar, José1 aPiña-García, C., A.1 aGershenson, Carlos  uhttp://dx.doi.org/10.1016/j.ecocom.2017.02.00201685nas a2200181   4500008004100000020001400041245006200055210006000117300000900177520113900186653003301325653001501358653001401373653002301387100002201410700002301432856004801455       2015                        eng d  a1936-644200aMeasuring the complexity of adaptive peer-to-peer systems0 aMeasuring the complexity of adaptive peertopeer systems  a1-163 aTo improve the efficiency of peer-to-peer (P2P) systems while adapting to changing environmental conditions, static peer-to-peer protocols can be replaced by adaptive plans. The resulting systems are inherently complex, which makes their development and characterization a challenge for traditional methods. Here we propose the design and analysis of adaptive P2P systems using measures of complexity, emergence, self-organization, and homeostasis based on information theory. These measures allow the evaluation of adaptive P2P systems and thus can be used to guide their design. We evaluate the proposal with a P2P computing system provided with adaptation mechanisms. We show the evolution of the system with static and also changing workload, using different fitness functions. When the adaptive plan forces the system to converge to a predefined performance level, the nodes may result in highly unstable configurations, which correspond to a high variance in time of the measured complexity. Conversely, if the adaptive plan is less ``aggressive'', the system may be more stable, but the optimal performance may not be achieved.10aAdaptive peer-to-peer system10aComplexity10aEvolution10aInformation theory1 aAmoretti, Michele1 aGershenson, Carlos  uhttp://dx.doi.org/10.1007/s12083-015-0385-4