COS 149-8
Ramification of spatial synchrony through a network of trophic interactions in the North Sea

Friday, August 14, 2015: 10:30 AM
343, Baltimore Convention Center
Daniel C Reuman, Department of Ecology and Evolutionary Biology and Kansas Biological Survey, University of Kansas, Lawrence, KS
Lawrence W. Sheppard, Department of Life Sciences, Imperial College Silwood Park, Ascot, United Kingdom
Background/Question/Methods

Coincident variation in the fluctuations of populations from different places is called population synchrony, and has been observed in many taxa in many locations. One main cause of population synchrony is environmental synchrony, i.e., spatially synchronous variation of environmental drivers – this is called the Moran effect. But Moran effects can be direct, where environmental drivers impact populations of the focal species, or could be mediated by biotic interactions - for instance, environmental drivers spatially synchronize populations of a predator species, and synchrony in that predator drives synchrony in a prey species. Little is known about the relative importance of direct Moran effects versus ramification of synchrony through complex community interaction networks; and little is known about the extent to which synchrony is a whole-community phenomenon as opposed to something that occurs independently for each species present. We developed wavelet statistical methods and applied them to data from multi-decadal, multi-species plankton and fish surveys of the whole North Sea to help answer these questions.

Results/Conclusions

We developed new spatial wavelet coherence methods and proved a wavelet version of the classic Moran theorem. One advantage of these techniques is they decompose synchrony and its causes by the timescales at which they occur, an important feature since if patterns and causes of synchrony differ by timescale, inferences using techniques that conflate timescales can be confounded. For 20 environmental variables, 23 plankton variables, and 29 fish variables, we created a series of matrices which relate synchrony in each variable to synchrony in each other such variable, separately for long (>4 years) and short (<=4 years) timescales. Matrices differed by timescale in important ways, indicating that processes by which synchrony ramifies through communities differ by timescale. There was a very large number of relationships, indicating that synchrony is a whole-community phenomenon. Some relationships were in phase, some were in anti-phase, and some were in quarter phase. The matrices are a new kind of ecological interaction network, and we compare their properties and uses to those of classic food web networks.