Population dynamics of synthetic Terraformation motifs

Ecosystems are complex systems, currently experiencing several threats associated with global warming, intensive exploitation and human-driven habitat degradation. Because of a general presence of multiple stable states, including states involving population extinction, and due to the intrinsic nonl...

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Detalles Bibliográficos
Autores: Solé, R., Montañez, R., Duran-Nebreda, S., Rodríguez-Amor, D., Vidiella, B., Sardanyés, J.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2018
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2072/377917
Acceso en línea:http://hdl.handle.net/2072/377917
Access Level:acceso abierto
Palabra clave:Matemàtiques
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Descripción
Sumario:Ecosystems are complex systems, currently experiencing several threats associated with global warming, intensive exploitation and human-driven habitat degradation. Because of a general presence of multiple stable states, including states involving population extinction, and due to the intrinsic nonlinearities associated with feedback loops, collapse inecosystems could occur in a catastrophic manner. It has been recently suggested that a potential path to prevent or modifythe outcome of these transitions would involve designing synthetic organisms and synthetic ecological interactions thatcould push these endangered systems out of the critical boundaries. In this paper, we investigate the dynamics of thesimplest mathematical models associated with four classes of ecological engineering designs, named Terraformation motifs(TMs). These TMs put in a nutshell different ecological strategies. In this context, some fundamental types of bifurcations pervade the systems'\'' dynamics. Mutualistic interactions can enhance persistence of the systems by means of saddle-node bifurcations. The models without cooperative interactions show that ecosystems achieve restoration through transcritical bifurcations. Thus, our analysis of the models allows us to define the stability conditions and parameter domains where these TMs must work.