Meta-ecosystem dynamics and functioning on finite spatial networks

Abstract

The addition of spatial structure to ecological concepts and theories has spurred integration between sub-disciplines within ecology, including community and ecosystem ecology. However, the complexity of spatial models limits their implementation to idealized, regular landscapes. We present a model meta-ecosystem with finite and irregular spatial structure consisting of local nutrient-autotrophs-herbivores ecosystems connected through spatial flows of materials and organisms. We study the effect of spatial flows on stability and ecosystem functions, and provide simple metrics of connectivity that can predict these effects. Our results show that high rates of nutrient and herbivore movement can destabilize local ecosystem dynamics, leading to spatially heterogeneous equilibria or oscillations across the metaecosystem, with generally increased meta-ecosystem primary and secondary production. However, the onset and the spatial scale of these emergent dynamics depend heavily on the spatial structure of the meta-ecosystem and on the relative movement rate of the autotrophs. We show how this strong dependence on finite spatial structure eludes commonly used metrics of connectivity, but can be predicted by the eigenvalues and eigenvectors of the connectivity matrix that describe the spatial structure and scale. Our study indicates the need to consider finite-size ecosystems in meta-ecosystem theory.

Beyond connectivity: how the structure of dispersal influences metacommunity dynamics

“…We further illustrate that differences in the pattern of connections and initial conditions among communities lead to the emergence of a wide array of stable asynchronous dynamics, leading to substantial differences in the potential persistence of an unstable predator-prey interaction at both the regional metacommunity and local patch level, despite the otherwise strict homogeneity of our metacommunities in which each community is identical and connected to exactly four other community patches. Our study is the first to produce this range of dynamical variation as a result of such subtle changes in spatial structure; this contrasts with earlier work that has only produced comparable variation through heterogeneity in connectivity or degree distribution (Holland and Hastings 2008;Gilarranz and Bascompte 2012), differences in dispersal among species (de Roos et al 1998), or alteration of community dynamics in more complex models (Marleau et al 2014;Hata et al 2014). The appearance of this striking range of dynamical variation, both in the frequency and and quality of asynchrony among metacommunities shows the important role of the pattern of connections among local communities in shaping the regional dynamics of metacommunities.…”

“…This is an important step to better understanding how metacommunity dynamics are influenced by spatial structure given the focus on connectivity in the literature (Bunn et al 2000;Marleau et al 2014;Plitzko and Drossel 2015;Saunders et al 1991;Taylor et al 1993). We further illustrate that differences in the pattern of connections and initial conditions among communities lead to the emergence of a wide array of stable asynchronous dynamics, leading to substantial differences in the potential persistence of an unstable predator-prey interaction at both the regional metacommunity and local patch level, despite the otherwise strict homogeneity of our metacommunities in which each community is identical and connected to exactly four other community patches.…”

“…Thus far it has been well established that synchronization is strongly influenced by the number of dispersal connections, or "connectivity," (Liebhold et al 2004;Paradis et al 1999;Holyoak and Lawler 1996) and the evenness of their distribution among patches, or the "degree" of each patch (Watts and Strogatz 1998;Holland and Hastings 2008;Gilarranz and Bascompte 2012). As a result, connectivity and related measures have been the focus in studies of structure and dynamics (Bunn et al 2000;Marleau et al 2014;Plitzko and Drossel 2015;Saunders et al 1991;Taylor et al 1993). However, such measures remove information about the patterning of connections among communities such as how often communities share neighbors, form tightly interconnected neighborhoods, and how distant communities are from these neighborhoods (Arenas et al 2008).…”

Nonhierarchical Dispersal Promotes Stability and Resilience in a Tritrophic Metacommunity

“…In those cases, hierarchically structured dispersal rates would actually act to suppress spatial patterns. More complex models have suggested that spatial coupling at other trophic levels or even with nutrients can lead to spatial patterning (Koelle and Vandermeer 2005;Marleau et al 2010Marleau et al , 2014, as adding additional species may shift which species are acting as activators or inhibitors. In systems with more than two species, the activator-inhibitor paradigm can be generalized to talk about sets of activators and inhibitors (Della Rossa et al 2012), but this still leaves the question, where in a food web do we expect to find activators or inhibitors, and therefore which dispersal structures can act to spatially stabilize ecosystems?…”

A primer on the history of food web ecology: Fundamental contributions of fourteen researchers

“…Perimeter:area ratio is especially important for islands that receive food web subsidies, with smaller islands having a greater per unit area effect of the subsidy. Each of these variables illustrates the importance of landscape ecology for understanding food web dynamics, a viewpoint that Polis pioneered decades ago and that continues to frame many research programs today (Marleau et al, 2014;Massol et al, 2011;.…”