Integrating modelling of biodiversity composition and ecosystem function
Mokany, K and Ferrier, S and Connolly, SR and Dunstan, PK and Fulton, EA and Harfoot, MB and Harwood, TD and Richardson, AJ and Roxburgh, SH and Scharlemann, JPW and Tittensor, DP and Westcott, DA and Wintle, BA, Integrating modelling of biodiversity composition and ecosystem function, Oikos, 125, (1) pp. 10-19. ISSN 0030-1299 (2016) [Refereed Article]
There is increasing reliance on ecological models to improve our understanding of how ecological systems work, to project likely outcomes under alternative global change scenarios and to help develop robust management strategies. Two common types of spatiotemporally explicit ecological models are those focussed on biodiversity composition and those focussed on ecosystem function. These modelling disciplines are largely practiced separately, with separate literature, despite growing evidence that natural systems are shaped by the interaction of composition and function. Here we call for the development of new modelling approaches that integrate composition and function, accounting for the important interactions between these two dimensions, particularly under rapid global change. We examine existing modelling approaches that have begun to combine elements of composition and function, identifying their potential contribution to fully integrated modelling approaches. The development and application of integrated models of composition and function face a number of important challenges, including biological data limitations, system knowledge and computational constraints. We suggest a range of promising avenues that could help researchers overcome these challenges, including the use of virtual species, macroecological relationships and hybrid correlative-mechanistic modelling. Explicitly accounting for the interactions between composition and function within integrated modelling approaches has the potential to improve our understanding of ecological systems, provide more accurate predictions of their future states and transform their management.