The power of models: mathematical approaches to the study of human–fauna interactions in the Pleistocene

Abstract

Understanding the complexity and dynamics of biological or ecological systems requires the inclusion of an abstract representation of the phenomena in the focus of interest. Indeed, a model is an abstract and simplified representation of a complex system in form of a narrative, a graph, a physical object, or a mathematical development. Narratives, i.e. verbal models, are the first step towards abstraction, and they are profusely used in palaeontology and archaeology to explain complex phenomena like biological dispersions (e.g. Koenigswald, 1992; van der Made, 1992; Agustí et al., 2009; Carbonell et al., 2010; Made and Mateos, 2010; Moncel, 2010; Muttoni et al., 2010; O'Regan et al., 2011; Palombo, 2013; Muttoni et al., 2014), human survival strategies (v.g. Hill, 1982; Speth, 1989; Bunn and Ezzo, 1993; Bunn and Pickering, 2010; Speth, 2010; Pobiner, 2015), human evolution (e.g. d’Errico and Sanchez Go~ni, 2003; Rosas, 2003; Finlayson et al., 2004, 2006; Foley and Gamble, 2009; Condemi and Weniger, 2011; Dennell et al., 2011; Bermúdez de Castro and Martin on-Torres, 2013), or ecosystem evolution and dynamics (e.g. Turner, 1992; Blumenschine et al., 1994; Brantingham and Kuhn, 2001; Van Valkenburgh and Sacco, 2002; Croitor and Brugal, 2010; Kahlke et al., 2011). Being useful as they are, verbal models have a number of disadvantages in comparison to formal models. Formal models usually go beyond questions that require only data interpretation and/or statistical analysis. They work in several situations, helping to evaluate empirical problems resulting from field or laboratory data and/or to propose theoretical settings based on initial assumptions (Jopp et al., 2011).