Details zur Publikation

Referenztyp Zeitschriften
DOI / URL Link
Volltext Autorenversion
Titel (primär) Harnessing uncertainty to approximate mechanistic models of interspecific interactions
Autor Clark, A.T.; Neuhauser, C.;
Journal / Serie Theoretical Population Biology
Erscheinungsjahr 2018
Department iDiv; PHYDIV;
Band/Volume 123
Sprache englisch;
POF III (gesamt) T11;
Keywords Lotka–Volterra competitive equations; Process noise; Model uncertainty; Interspecific competition; Model abstraction; Interspecific tradeoff
Abstract Because the Lotka–Volterra competitive equations posit no specific competitive mechanisms, they are exceedingly general, and can theoretically approximate any underlying mechanism of competition near equilibrium. In practice, however, these models rarely generate accurate predictions in diverse communities. We propose that this difference between theory and practice may be caused by how uncertainty propagates through Lotka–Volterra systems. In approximating mechanistic relationships with Lotka–Volterra models, associations among parameters are lost, and small variation can correspond to large and unrealistic changes in predictions. We demonstrate that constraining Lotka–Volterra models using correlations among parameters expected from hypothesized underlying mechanisms can reintroduce some of the underlying structure imposed by those mechanisms, thereby improving model predictions by both reducing bias and increasing precision. Our results suggest that this hybrid approach may combine some of the generality of phenomenological models with the broader applicability and meaningful interpretability of mechanistic approaches. These methods could be useful in poorly understood systems for identifying important coexistence mechanisms, or for making more accurate predictions.
ID 20972
dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=20972
Clark, A.T., Neuhauser, C. (2018):
Harnessing uncertainty to approximate mechanistic models of interspecific interactions
Theor. Popul. Biol. 123 , 35 - 44