While previous studies have evaluated the change in stability for the addition or removal of individual species from trophic food chains and food webs, we know of no study that presents a general theory for how stability changes with the addition or removal of trophic levels. In this study, we present a simple model of a linear food chain and systematically evaluate how stability—measured as invariability—changes with the addition or removal of trophic levels. We identify the presence of trophic cascades in the stability of species. Owing to top-down control by predation and bottom-up regulation by prey, we find that stability of a species is highest when it is at the top of the food chain and lowest when it is just under the top of the food chain. Thus, stability shows patterns identical to those of mean biomass with the addition or removal of trophic levels in food chains. Our results provide a baseline towards a general theory of the effect of adding or removing trophic levels on stability, which can be used to inform empirical studies.

Network theory is finding applications in the life and social sciences for ecology, epidemiology, finance and social–ecological systems. While there are methods to generate specific types of networks, the broad literature is focused on generatingunweightednetworks. In this paper, we present a framework for generatingweightednetworks that satisfy user-defined criteria. Each criterion hierarchically defines a feature of the network and, in doing so, complements existing algorithms in the literature. We use a general example of ecological species dispersal to illustrate the method and provide open-source code for academic purposes.