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AbstractNonliving resources frequently flow across ecosystem boundaries, which can yield networks of spatially coupled ecosystems. Yet the significance of resource flows for ecosystem function has predominantly been understood by studying two or a few coupled ecosystems, overlooking the broader resource flow network and its spatial structure. Here, we investigate how the spatial structure of larger resource flow networks influences ecosystem function at metaecosystem scales by analyzing metaecosystem models with homogeneously versus heterogeneously distributed resource flow networks but otherwise identical characteristics. We show that metaecosystem function can differ strongly between metaecosystems with contrasting resource flow networks. Differences in function generally arise through the scaling up of nonlinear local processes interacting with spatial variation in local dynamics, the latter of which is influenced by network structure. However, we find that neither network structure guarantees the greatest metaecosystem function. Rather, biotic (organism traits) and abiotic (resource flow rates) properties interact with network structure to determine which yields greater metaecosystem function. Our findings suggest that the spatial structure of resource flow networks coupling ecosystems can be a driver of ecosystem function at landscape scales. Furthermore, our study demonstrates how modifications to the structural, biotic, or abiotic properties of metaecosystem networks can have nontrivial large-scale effects on ecosystem function.

Ecosystems are linked to neighbouring ecosystems not only by dispersal, but also by the movement of subsidy. Such subsidy couplings between ecosystems have important landscape-scale implications because perturbations in one ecosystem may affect community structure and functioning in neighbouring ecosystems via increased/decreased subsidies. Here, we combine a general theoretical approach based on harvesting theory and a two-patch protist meta-ecosystem experiment to test the effect of regional perturbations on local community dynamics. We first characterized the relationship between the perturbation regime and local population demography on detritus production using a mathematical model. We then experimentally simulated a perturbation gradient affecting connected ecosystems simultaneously, thus altering cross-ecosystem subsidy exchanges. We demonstrate that the perturbation regime can interact with local population dynamics to trigger unexpected temporal variations in subsidy pulses from one ecosystem to another. High perturbation intensity initially led to the highest level of subsidy flows; however, the level of perturbation interacted with population dynamics to generate a crash in subsidy exchange over time. Both theoretical and experimental results show that a perturbation regime interacting with local community dynamics can induce a collapse in population levels for recipient ecosystems. These results call for integrative management of human-altered landscapes that takes into account regional dynamics of both species and resource flows., (© 2016 The Author(s).)

As societal demand for food, water and other life-sustaining resources grows, the science of ecosystem services (ES) is seen as a promising tool to improve our understanding, and ultimately the management, of increasingly uncertain supplies of critical goods provided or supported by natural ecosystems. This promise, however, is tempered by a relatively primitive understanding of the complex systems supporting ES, which as a result are often quantified as static resources rather than as the dynamic expression of human-natural systems. This article attempts to pinpoint the minimum level of detail that ES science needs to achieve in order to usefully inform the debate on environmental securities, and discusses both the state of the art and recent methodological developments in ES in this light. We briefly review the field of ES accounting methods and list some desiderata that we deem necessary, reachable and relevant to address environmental securities through an improved science of ES. We then discuss a methodological innovation that, while only addressing these needs partially, can improve our understanding of ES dynamics in data-scarce situations. The methodology is illustrated and discussed through an application related to water security in the semi-arid landscape of the Great Ruaha river of Tanzania.