title: An Entangled Model for Sustainability Indicators.
abstract: Nowadays the challenge for humanity is to find pathways towards sustainable development. Decision makers require a set of sustainability indicators to know if the sustainability strategies are following those pathways. There are more than one hundred sustainability indicators but they differ on their relative importance according to the size of the locality and change on time. The resources needed to follow these sustainability indicators are scarce and in some instances finite, especially in smaller regions. Therefore strategies to select set of these indicators are useful for decision makers responsible for monitoring sustainability. In this paper we propose a model for the identification and selection of a set of sustainability indicators that adequately represents human systems. In developing this model, we applied evolutionary dynamics in a space where sustainability indicators are fundamental entities interconnected by an interaction matrix. we used a fixed interaction that simulates the current context for the city of Cuernavaca, México as an example. We were able to identify and define relevant sets indicators for the system by using the Pareto principle. In this case we identified a set of sixteen sustainability indicators with more than 80% of the total strength. This set presents resilience to perturbations. For the Tangled Nature framework we provided a manner of treating different contexts (i.e., cities, counties, states, regions, countries, continents or the whole planet), dealing with small dimensions. This model provides decision makers with a valuable tool to select sustainability indicators set for towns, cities, regions, countries, continents or the entire planet according to a coevolutionary framework. The social legitimacy can arise from the fact that each individual indicator must be selected from those that are most important for the subject community.
authors: Instituto de Investigación en Ciencias Básicas y Aplicadas, Universidad Autónoma del Estado de Morelos, Cuernavaca, Morelos, México.
authors: Pável
authors: P
authors: Vázquez
authors: Instituto de Energías Renovables y Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Temixco, Morelos, México.
authors: Jesús A
authors: JA
authors: Del Río
authors: InnoBa, Cuernavaca, Morelos, México.
authors: Karla G
authors: KG
authors: Cedano
authors: Instituto de Energías Renovables, Universidad Nacional Autónoma de México, Temixco, Morelos, México.
authors: Manuel
authors: M
authors: Martínez
authors: Department of Mathematics and Center for Complexity Science, Imperial College London, London, United Kingdom.
authors: Henrik J
authors: HJ
authors: Jensen
mesh_terms: D002947:Cities / Q000191:economics; D003247:Conservation of Natural Resources / Q000191:economics / Q000706:statistics & numerical data*; D006801:Humans; D008800:Mexico; D015233:Models, Statistical