Evolution of and in complex ecological networks

Background/Question/Methods

Species have long been recognized to emerge and evolve in complex ecological networks.  Over 150 years ago, Darwin concluded his "Origin of Species" by describing a "tangled bank" of diverse interacting species that "have all been produced by laws acting around us."  However, study of such emergence and evolution rarely embraces complex ecological networks in a realistic manner.  Increasing understanding of the structure and function of these networks and more powerful computational approaches can help address this short coming.   We applied such understanding and approaches to speciation within realistically structured and nonlinearly dynamic networks with up to 100 species.  Speciation was initiated by modifying small amounts of a parent species' biomass.  The traits of these small amounts of "hopeful monster" biomass were assigned by stochastically changing parent species traits such as body size, diet, and consumers.  We studied such in silico evolution of species and their effects on the network within which they emerged over thousands of time steps among hundreds of networks experiencing hundreds of potential speciation events.

Results/Conclusions

We found that speciation in networks with less than ten species typically caused more species to go extinct than were speciated due to mechanisms such as competitive exclusion and other dynamic instabilities.   However, in network with 15 or more species, successful speciation was more frequent and networks more consistently evolved into much larger networks.  Still, while diversity increased, evolved networks lacked many of the larger, highly general, and high trophic level consumers typically found in empirical food webs.   We speculate that increased attention to the biotically critical distinction between plant and animal biomass  is needed to address this short coming.  Still the level of realism including the abundance distributions among species and other properties suggests that our models are powerful tools for further explorations of evolution within, and of, complex ecological networks.