Abstract
The stability of ecological systems has been a long-standing focus of ecology. Recently, tools from random matrix theory have identified the main drivers of stability in ecological communities whose network structure is random. However, empirical food webs differ greatly from random graphs. For example, their degree distribution is broader, they contain few trophic cycles, and they are almost interval. Here we derive an approximation for the stability of food webs whose structure is generated by the cascade model, in which ‘larger' species consume ‘smaller' ones. We predict the stability of these food webs with great accuracy, and our approximation also works well for food webs whose structure is determined empirically or by the niche model. We find that intervality and broad degree distributions tend to stabilize food webs, and that average interaction strength has little influence on stability, compared with the effect of variance and correlation.
Highlights
The stability of ecological systems has been a long-standing focus of ecology
We show numerically that our approximation estimates the stability of these food webs with great accuracy, and that similar results are obtained when we generate food webs starting from empirical data, or when using the niche model[10]
We show that intervality and broad degree distributions tend to stabilize food webs, and we highlight a counterintuitive result: research on the relationship between stability and the distribution of interaction strengths has historically focused on average strength[11,12,13,14], we show that its role in determining stability is small, compared with that of variance and correlation
Summary
The stability of ecological systems has been a long-standing focus of ecology. Recently, tools from random matrix theory have identified the main drivers of stability in ecological communities whose network structure is random. In empirical webs the degree distribution, describing the number of partners each species interact with, is much broader[6] than in random graphs; the webs contain only a handful of trophic cycles[7] (in which, for example, species a consumes b, b consumes c and c consumes a), while random graphs with the same number of links would contain many more; empirical webs are almost interval—there is a way to order all species such that consumers tend to prey on consecutive species in the hierarchy[8] To overcome this limitation, we derive an approximation for the stability of food webs whose structure is generated by the cascade model[9], which assumes that species can be ordered such that ‘larger’ species consume ‘smaller’ ones. We show that intervality and broad degree distributions tend to stabilize food webs, and we highlight a counterintuitive result: research on the relationship between stability and the distribution of interaction strengths has historically focused on average strength[11,12,13,14], we show that its role in determining stability is small, compared with that of variance and correlation
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
