@article {165,
	title = {Complexity of lakes in a latitudinal gradient},
	journal = {Ecological Complexity},
	volume = {31},
	year = {2017},
	month = {9},
	pages = {1{\textendash}20},
	abstract = {Measuring 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{\textquoteright} 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.},
	keywords = {Autopoiesis, Biocomplexity, Emergence, Homeostasis, Information theory, Self-organization},
	isbn = {1476-945X},
	doi = {10.1016/j.ecocom.2017.02.002},
	url = {http://dx.doi.org/10.1016/j.ecocom.2017.02.002},
	author = {Fern{\'a}ndez, Nelson and Aguilar, Jos{\'e} and Pi{\~n}a-Garc{\'\i}a, C. A. and Gershenson, Carlos}
}
@article {151,
	title = {Measuring the complexity of adaptive peer-to-peer systems},
	journal = {Peer-to-Peer Networking and Applications},
	year = {2015},
	pages = {1-16},
	abstract = {To 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 {\textquoteleft}{\textquoteleft}aggressive{\textquoteright}{\textquoteright}, the system may be more stable, but the optimal performance may not be achieved.},
	keywords = {Adaptive peer-to-peer system, Complexity, Evolution, Information theory},
	isbn = {1936-6442},
	doi = {10.1007/s12083-015-0385-4},
	url = {http://dx.doi.org/10.1007/s12083-015-0385-4},
	author = {Amoretti, Michele and Gershenson, Carlos}
}
