Details zur Publikation

Referenztyp Zeitschriften
DOI / URL Link
Titel (primär) Per aspera ad astra: through complex population modeling to predictive theory
Autor Topping, C.J.; Alrøe, H.F.; Farrell, K.N.; Grimm, V.;
Journal / Serie American Naturalist
Erscheinungsjahr 2015
Department OESA; iDiv;
Band/Volume 186
Heft 5
Sprache englisch;
POF III (gesamt) T11;
Keywords complexity; error avoidance; agent-based models; model development; modest approach
UFZ Querschnittsthemen RU5;
Abstract Population models in ecology are often not good at predictions, even if they are complex and seem to be realistic enough. The reason for this might be that Occam’s razor, which is key for minimal models exploring ideas and concepts, has been too uncritically adopted for more realistic models of systems. This can tie models too closely to certain situations, thereby preventing them from predicting the response to new conditions. We therefore advocate a new kind of parsimony to improve the application of Occam’s razor. This new parsimony balances two contrasting strategies for avoiding errors in modeling: avoiding inclusion of nonessential factors (false inclusions) and avoiding exclusion of sometimes-important factors (false exclusions). It involves a synthesis of traditional modeling and analysis, used to describe the essentials of mechanistic relationships, with elements that are included in a model because they have been reported to be or can arguably be assumed to be important under certain conditions. The resulting models should be able to reflect how the internal organization of populations change and thereby generate representations of the novel behavior necessary for complex predictions, including regime shifts.
ID 16595
dauerhafte UFZ-Verlinkung
Topping, C.J., Alrøe, H.F., Farrell, K.N., Grimm, V. (2015):
Per aspera ad astra: through complex population modeling to predictive theory
Am. Nat. 186 (5), 669 - 674