Massachusetts Institute of Technology, United States
Background/Question/Methods Effective conservation of ecological communities requires accurate and up-to-date information about whether species are persisting or declining to extinction. The persistence of ecological communities is largely supported by its structured architecture of species interactions, known as an ecological network. While the network is the most relevant scale for network persistence, in practice, we can only monitor small subsets of these networks due to logistical sampling constraints.
Results/Conclusions Here, we show that the persistence of these small subnetworks in isolation --- that is, their persistence when considered separately from the larger network of which they are a part --- is a reliable probabilistic indicator of the persistence of the network as a whole. Theoretically, this finding is based on an emergent principle of organization showing that a network is expected to persist under changing conditions when at least half of its randomly sampled subnetworks satisfy the persistence-in-isolation criterion. Our results hold for both antagonistic and mutualistic interaction networks. We provide a Bayesian method for updating our belief that monitored networks are persistent. Empirically, we show that our theoretical predictions are supported by data on invaded networks contrasting restored and unrestored areas, even in the presence of environmental variability. Our work suggests that coordinated action to aggregate information from incomplete sampling can provide a means to rapidly assess the persistence of entire ecological networks and the expected success of restoration strategies.