Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/129239
Título: A strategic roadmap for interdisciplinary modeling in ecology: the result of reading ‘Defining an ecological equation of state: Response to Riera et al. 2023′ (Newman et al., 2023)
Autores/as: Riera, Rodrigo 
Fath, Brian D.
Herrera, Ada M.
Rodríguez, Ricardo A.
Clasificación UNESCO: 251007 Oceanografía física
251001 Oceanografía biológica
1206 Análisis numérico
120602 Ecuaciones diferenciales
Palabras clave: Ecological equation Of state
Interdisciplinary modeling
Maxent algorithm
Organic biophysics of ecosystems
Species diversity, et al.
Fecha de publicación: 2024
Publicación seriada: Ecological Modelling 
Resumen: An interesting dialogue is developed between Newman et al. (2023) and Riera et al. (2023), in which proposals related to the development of equations of state in ecosystem ecology are discussed in depth. This debate is more important than it first appears, since the persistent gap between theoretical and empirical ecology is due, in part, to the absence of a comprehensive paradigm in this field. As it is exemplified in the first section of this article, a sequence of models derived from a reliable equation of state would help to bridge the aforementioned gap. Although this manuscript is analytically monolithic, five main thematic strands can be identified: (i) Examination of the objections of Newman et al. (2023), juxtaposing them with key concepts from ecology, information theory, physics and the MaxEnt algorithm. (ii) Validation of the criteria in (i) through theoretical and data-based examples. (iii) Interdisciplinary linkages between (i) and (ii). (iv) Epistemological generalizations from the previous strands to obtain a strategic roadmap for interdisciplinary modeling in ecology. (v) Conclusions referred to the general meaning of points (i) and (ii). On a general level, our objective is that this manuscript will go beyond a simple academic debate, being useful for colleagues interested in interdisciplinary modeling.
URI: http://hdl.handle.net/10553/129239
ISSN: 0304-3800
DOI: 10.1016/j.ecolmodel.2024.110658
Fuente: Ecological Modelling [ISSN 0304-3800], v. 490
Colección:Artículos
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