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| Open AccessMultilayer networks reveal the spatial structure of seed-dispersal interactions across the Great Rift landscapes
Species interaction networks have been usually delimited by perceived habitat borders. Here, seed-dispersal is analyzed as a regional multilayer network of interconnected habitats, highlighting the key role of versatile dispersers for the functional cohesion of the whole Gorongosa landscape.
- Sérgio Timóteo
- , Marta Correia
- & Ruben Heleno
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Article
| Open AccessMapping the ecological networks of microbial communities
Understanding ecological interactions in microbial communities is limited by lack of informative longitudinal abundance data necessary for reliable inference. Here, Xiao et al. develop a method to infer the interactions between microbes based on their abundances in steady-state samples.
- Yandong Xiao
- , Marco Tulio Angulo
- & Yang-Yu Liu
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Article
| Open AccessPredicting the effect of habitat modification on networks of interacting species
In a changing world, the ability to predict the impact of environmental change on ecological communities is essential. Here, the authors show that by separating species abundances from interaction preferences, they can predict the effects of habitat modification on the structure of weighted species interaction networks, even with limited data.
- Phillip P. A. Staniczenko
- , Owen T. Lewis
- & Felix Reed-Tsochas
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Article
| Open AccessFeasibility and coexistence of large ecological communities
A central question in theoretical ecology is how diverse species can coexist in communities, and how that coexistence depends on network properties. Here, Grilliet al. quantify the extent of feasible coexistence of empirical networks, showing that it is smaller for trophic than mutualism networks.
- Jacopo Grilli
- , Matteo Adorisio
- & Amos Maritan
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| Open AccessMutualism supports biodiversity when the direct competition is weak
Theoretical ecologists have made disparate predictions regarding the relationship between mutualism and stability. Here, Pascual-García and Bastolla develop a theoretical framework showing that model mutualistic interactions promote structural stability when competition is weaker than a threshold depending on network architecture.
- Alberto Pascual-García
- & Ugo Bastolla
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Article
| Open AccessEcological networks are more sensitive to plant than to animal extinction under climate change
In addition to affecting individual species, climate change can modify species interactions. Coupling simulation models with networks between plants and animal pollinators and seed dispersers, Schleuninget al. show that animal persistence under climate change depends more strongly on plant persistence than vice versa.
- Matthias Schleuning
- , Jochen Fründ
- & Christian Hof
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| Open AccessAnimal diversity and ecosystem functioning in dynamic food webs
Losing animals from food webs could reduce ecosystem function, but drivers of this pattern are difficult to disentangle. With food web simulations, Schneider et al. show that high animal diversity does not release plants from top-down control owing to a balancing effect of increased animal body size.
- Florian D. Schneider
- , Ulrich Brose
- & Christian Guill
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| Open AccessThe Google matrix controls the stability of structured ecological and biological networks
May showed that ecosystem stability decreases above some threshold complexity. Here, Stone generalizes May’s random matrix approach to realistic species interaction networks through a Google-matrix reduction scheme, and provides an explanation for why feasible ecological networks are usually stable.
- Lewi Stone
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| Open AccessApparent competition drives community-wide parasitism rates and changes in host abundance across ecosystem boundaries
Species sharing a common enemy such as a parasitoid or predator can indirectly affect one another. Here, Frost et al. use quantitative food-web data from communities of caterpillar hosts to show experimentally that apparent competition is important in predicting food-web structure across habitats.
- Carol M. Frost
- , Guadalupe Peralta
- & Jason M. Tylianakis
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Article
| Open AccessEnvironmental change makes robust ecological networks fragile
Despite their complexity, ecological networks appear robust to species loss. Here, Strona and Lafferty use artificial life simulations and real-world data to show that such robustness applies to stable conditions, but can collapse when the environment changes.
- Giovanni Strona
- & Kevin D. Lafferty
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Article
| Open AccessEffect of localization on the stability of mutualistic ecological networks
The architecture of ecological interaction networks affects community dynamics. Here, Suweis et al.show that mutualistic networks are characterized by a high degree of localization, and that localization reduces perturbation propagation and attenuates its impact on species abundances.
- Samir Suweis
- , Jacopo Grilli
- & Amos Maritan
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Coupling unstable agents in biological control
Control of pests in agriculture by introduced natural enemies may be hampered because of unstable oscillations in the dynamics of the two populations. Here, the authors show that stable conditions can be maintained by combining two unstable systems utilizing different biological control agents.
- Theresa Wei Ying Ong
- & John H. Vandermeer
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Estimating the tolerance of species to the effects of global environmental change
Global environmental change is affecting the strength of interspecific interactions. The authors here estimate how much change species can tolerate before becoming extinct, and they find that species tolerance is very sensitive to the net direction of change.
- Serguei Saavedra
- , Rudolf P. Rohr
- & Jordi Bascompte
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The ghost of nestedness in ecological networks
A nested pattern of interactions is thought to promote species persistence in mutualistic ecological networks. In this study, Staniczenko et al. introduce a spectral graph measure of nestedness, to show that nestedness is maximally destabilizing and demonstrate that empirical species preferences are not quantitatively nested.
- Phillip P. A. Staniczenko
- , Jason C. Kopp
- & Stefano Allesina